GRDB 2 Swift Platforms License Build Status

A toolkit for SQLite databases, with a focus on application development

Latest release: February 25, 2018 • version 2.9.0 • CHANGELOG

Requirements: iOS 8.0+ / OSX 10.9+ / watchOS 2.0+ • Swift 4.0 / Xcode 9+

Swift version GRDB version
Swift 4 v2.9.0
Swift 3.2 v1.3.0
Swift 3.1 v1.3.0
Swift 3 v1.0
Swift 2.3 v0.81.2
Swift 2.2 v0.80.2

Follow @groue on Twitter for release announcements and usage tips.

What is this?

GRDB provides raw access to SQL and advanced SQLite features, because one sometimes enjoys a sharp tool. It has robust concurrency primitives, so that multi-threaded applications can efficiently use their databases. It grants your application models with persistence and fetching methods, so that you don’t have to deal with SQL and raw database rows when you don’t want to.

Compared to SQLite.swift or FMDB, GRDB can spare you a lot of glue code. Compared to Core Data or Realm, it can simplify your multi-threaded applications.

It comes with up-to-date documentation, general articles, sample code, and a lot of interesting resolved issues that may answer your eventual questions and foster best practices.

For more information, check out:

Features • Usage • Installation • Documentation • FAQ

Features

GRDB ships with:

Companion libraries that enhance and extend GRDB:

  • RxGRDB: track database changes in a reactive way, with RxSwift.
  • GRDBObjc: FMDB-compatible bindings to GRDB.

More than a set of tools that leverage SQLite abilities, GRDB is also:

Usage

Open a connection to the database:

import GRDB

// Simple database connection
let dbQueue = try DatabaseQueue(path: "/path/to/database.sqlite")

// Enhanced multithreading based on SQLite's WAL mode
let dbPool = try DatabasePool(path: "/path/to/database.sqlite")

Execute SQL statements:

try dbQueue.inDatabase { db in
    try db.execute("""
        CREATE TABLE places (
          id INTEGER PRIMARY KEY,
          title TEXT NOT NULL,
          favorite BOOLEAN NOT NULL DEFAULT 0,
          latitude DOUBLE NOT NULL,
          longitude DOUBLE NOT NULL)
        """)

    try db.execute("""
        INSERT INTO places (title, favorite, latitude, longitude)
        VALUES (?, ?, ?, ?)
        """, arguments: ["Paris", true, 48.85341, 2.3488])

    let parisId = db.lastInsertedRowID
}

Fetch database rows and values:

try dbQueue.inDatabase { db in
    let rows = try Row.fetchCursor(db, "SELECT * FROM places")
    while let row = try rows.next() {
        let title: String = row["title"]
        let isFavorite: Bool = row["favorite"]
        let coordinate = CLLocationCoordinate2D(
            latitude: row["latitude"],
            longitude: row["longitude"])
    }

    let placeCount = try Int.fetchOne(db, "SELECT COUNT(*) FROM places")! // Int
    let placeTitles = try String.fetchAll(db, "SELECT title FROM places") // [String]
}

// Extraction
let placeCount = try dbQueue.inDatabase { db in
    try Int.fetchOne(db, "SELECT COUNT(*) FROM places")!
}

Insert and fetch records:

struct Place {
    var id: Int64?
    var title: String
    var isFavorite: Bool
    var coordinate: CLLocationCoordinate2D
}

// snip: turn Place into a "record" by adopting the protocols that
// provide fetching and persistence methods.

try dbQueue.inDatabase { db in
    var berlin = Place(
        id: nil,
        title: "Berlin",
        isFavorite: false,
        coordinate: CLLocationCoordinate2D(latitude: 52.52437, longitude: 13.41053))

    try berlin.insert(db)
    berlin.id // some value

    berlin.isFavorite = true
    try berlin.update(db)

    // Fetch [Place] from SQL
    let places = try Place.fetchAll(db, "SELECT * FROM places")
}

Avoid SQL with the query interface:

try dbQueue.inDatabase { db in
    try db.create(table: "places") { t in
        t.column("id", .integer).primaryKey()
        t.column("title", .text).notNull()
        t.column("favorite", .boolean).notNull().defaults(to: false)
        t.column("longitude", .double).notNull()
        t.column("latitude", .double).notNull()
    }

    // Place?
    let paris = try Place.fetchOne(db, key: 1)

    // Place?
    let titleColumn = Column("title")
    let berlin = try Place.filter(titleColumn == "Berlin").fetchOne(db)

    // [Place]
    let favoriteColumn = Column("favorite")
    let favoritePlaces = try Place
        .filter(favoriteColumn)
        .order(titleColumn)
        .fetchAll(db)
}

Documentation

GRDB runs on top of SQLite: you should get familiar with the SQLite FAQ. For general and detailed information, jump to the SQLite Documentation.

Reference

Getting Started

SQLite and SQL

Records and the Query Interface

Application Tools

Good to Know

FAQ

Sample Code

Installation

The installation procedures below have GRDB use the version of SQLite that ships with the target operating system.

See Encryption for the installation procedure of GRDB with SQLCipher.

See Custom SQLite builds for the installation procedure of GRDB with a customized build of SQLite 3.22.0.

CocoaPods

CocoaPods is a dependency manager for Xcode projects. To use GRDB with CocoaPods (version 1.2 or higher), specify in your Podfile:

use_frameworks!
pod 'GRDB.swift'

Swift Package Manager

The Swift Package Manager automates the distribution of Swift code. To use GRDB with SPM, add a dependency to your Package.swift file:

let package = Package(
    dependencies: [
        .package(url: "https://github.com/groue/GRDB.swift.git", from: "2.9.0")
    ]
)

Note that Linux is not currently supported.

Carthage

Carthage can build GRDB frameworks, but it can also inexplicably fail. This installation method is thus unsupported.

If you decide to use Carthage despite this warning, and get any Carthage-related error, please open an issue in the Carthage repo, ask Stack Overflow, summon your local Xcode guru, or submit a pull request that has the make test_CarthageBuild command succeed 100% of the time (one time is not enough). See #262 for more information.

Manually

  1. Download a copy of GRDB, or clone its repository and make sure you use the latest tagged version with the git checkout v2.9.0 command.

  2. Embed the GRDB.xcodeproj project in your own project.

  3. Add the GRDBOSX, GRDBiOS, or GRDBWatchOS target in the Target Dependencies section of the Build Phases tab of your application target (extension target for WatchOS).

  4. Add the GRDB.framework from the targetted platform to the Embedded Binaries section of the General tab of your application target (extension target for WatchOS).

See GRDBDemoiOS for an example of such integration.

Database Connections

GRDB provides two classes for accessing SQLite databases: DatabaseQueue and DatabasePool:

import GRDB

// Pick one:
let dbQueue = try DatabaseQueue(path: "/path/to/database.sqlite")
let dbPool = try DatabasePool(path: "/path/to/database.sqlite")

The differences are:

  • Database pools allow concurrent database accesses (this can improve the performance of multithreaded applications).
  • Unless read-only, database pools open your SQLite database in the WAL mode.
  • Database queues support in-memory databases.

If you are not sure, choose DatabaseQueue. You will always be able to switch to DatabasePool later.

Database Queues

Open a database queue with the path to a database file:

import GRDB

let dbQueue = try DatabaseQueue(path: "/path/to/database.sqlite")
let inMemoryDBQueue = DatabaseQueue()

SQLite creates the database file if it does not already exist. The connection is closed when the database queue gets deallocated.

A database queue can be used from any thread. The inDatabase and inTransaction methods are synchronous, and block the current thread until your database statements are executed in a protected dispatch queue. They safely serialize the database accesses:

// Execute database statements:
try dbQueue.inDatabase { db in
    try db.create(table: "places") { ... }
    try Place(...).insert(db)
}

// Wrap database statements in a transaction:
try dbQueue.inTransaction { db in
    if let place = try Place.fetchOne(db, key: 1) {
        try place.delete(db)
    }
    return .commit
}

// Read values:
try dbQueue.inDatabase { db in
    let places = try Place.fetchAll(db)
    let placeCount = try Place.fetchCount(db)
}

// Extract a value from the database:
let placeCount = try dbQueue.inDatabase { db in
    try Place.fetchCount(db)
}

A database queue needs your application to follow rules in order to deliver its safety guarantees. Please refer to the Concurrency chapter.

See DemoApps/GRDBDemoiOS/AppDatabase.swift for a sample code that sets up a database queue on iOS.

DatabaseQueue Configuration

var config = Configuration()
config.readonly = true
config.foreignKeysEnabled = true // Default is already true
config.trace = { print($0) }     // Prints all SQL statements

let dbQueue = try DatabaseQueue(
    path: "/path/to/database.sqlite",
    configuration: config)

See Configuration for more details.

Database Pools

A Database Pool allows concurrent database accesses.

When more efficient than database queues, database pools also inherit the subtleties of SQLite’s WAL mode. If you don’t feel comfortable with improving your SQLite skills, use a database queue instead.

import GRDB
let dbPool = try DatabasePool(path: "/path/to/database.sqlite")

SQLite creates the database file if it does not already exist. The connection is closed when the database pool gets deallocated.

:point_up: Note: unless read-only, a database pool opens your database in the SQLite WAL mode. The WAL mode does not fit all situations. Please have a look at https://www.sqlite.org/wal.html.

A database pool can be used from any thread. The read, write and writeInTransaction methods are synchronous, and block the current thread until your database statements are executed in a protected dispatch queue. They safely isolate the database accesses:

// Execute database statements:
try dbPool.write { db in
    try db.create(table: "places") { ... }
    try Place(...).insert(db)
}

// Wrap database statements in a transaction:
try dbPool.writeInTransaction { db in
    if let place = try Place.fetchOne(db, key: 1) {
        try place.delete(db)
    }
    return .commit
}

// Read values:
try dbPool.read { db in
    let places = try Place.fetchAll(db)
    let placeCount = try Place.fetchCount(db)
}

// Extract a value from the database:
let placeCount = try dbPool.read { db in
    try Place.fetchCount(db)
}

Database pools allow several threads to access the database at the same time:

  • When you don’t need to modify the database, prefer the read method, because several threads can perform reads in parallel.

    Reads are generally non-blocking, unless the maximum number of concurrent reads has been reached. In this case, a read has to wait for another read to complete. That maximum number can be configured.

  • Unlike reads, writes are serialized. There is never more than a single thread that is writing into the database.

  • Reads are guaranteed an immutable view of the last committed state of the database, regardless of concurrent writes. This kind of isolation is called snapshot isolation.

    To provide read closures an immutable view of the last executed writing block as a whole, use writeInTransaction instead of write.

  • Database pools can take snapshots of the database.

See Differences between Database Queues and Pools before you decide to use a database pool. When you’re sure, see Advanced DatabasePool for more DatabasePool hotness.

A database pool needs your application to follow rules in order to deliver its safety guarantees. Please refer to the Concurrency chapter.

For a sample code that sets up a database pool on iOS, see DemoApps/GRDBDemoiOS/AppDatabase.swift, and replace DatabaseQueue with DatabasePool.

DatabasePool Configuration

var config = Configuration()
config.readonly = true
config.foreignKeysEnabled = true // Default is already true
config.trace = { print($0) }     // Prints all SQL statements
config.maximumReaderCount = 10   // The default is 5

let dbPool = try DatabasePool(
    path: "/path/to/database.sqlite",
    configuration: config)

See Configuration for more details.

Database pools are more memory-hungry than database queues. See Memory Management for more information.

SQLite API

In this section of the documentation, we will talk SQL. Jump to the query interface if SQL is not your cup of tea.

Advanced topics:

Executing Updates

Once granted with a database connection, the execute method executes the SQL statements that do not return any database row, such as CREATE TABLE, INSERT, DELETE, ALTER, etc.

For example:

try dbQueue.inDatabase { db in
    try db.execute("""
        CREATE TABLE players (
            id INTEGER PRIMARY KEY,
            name TEXT NOT NULL,
            score INT)
        """)

    try db.execute(
        "INSERT INTO players (name, score) VALUES (:name, :score)",
        arguments: ["name": "Barbara", "score": 1000])

    // Join multiple statements with a semicolon:
    try db.execute("""
        INSERT INTO players (name, score) VALUES (?, ?);
        INSERT INTO players (name, score) VALUES (?, ?)
        """, arguments: ["Arthur", 750, "Barbara", 1000])
}

The ? and colon-prefixed keys like :name in the SQL query are the statements arguments. You pass arguments with arrays or dictionaries, as in the example above. See Values for more information on supported arguments types (Bool, Int, String, Date, Swift enums, etc.).

Never ever embed values directly in your SQL strings, and always use arguments instead. See Avoiding SQL Injection for more information.

After an INSERT statement, you can get the row ID of the inserted row:

try db.execute(
    "INSERT INTO players (name, score) VALUES (?, ?)",
    arguments: ["Arthur", 1000])
let playerId = db.lastInsertedRowID

Don’t miss Records, that provide classic persistence methods:

let player = Player(name: "Arthur", score: 1000)
try player.insert(db)
let playerId = player.id

Fetch Queries

Database connections let you fetch database rows, plain values, and custom models aka records.

Rows are the raw results of SQL queries:

try dbQueue.inDatabase { db in
    if let row = try Row.fetchOne(db, "SELECT * FROM wines WHERE id = ?", arguments: [1]) {
        let name: String = row["name"]
        let color: Color = row["color"]
        print(name, color)
    }
}

Values are the Bool, Int, String, Date, Swift enums, etc. stored in row columns:

try dbQueue.inDatabase { db in
    let urls = try URL.fetchCursor(db, "SELECT url FROM wines")
    while let url = try urls.next() {
        print(url)
    }
}

Records are your application objects that can initialize themselves from rows:

let wines = try dbQueue.inDatabase { db in
    try Wine.fetchAll(db, "SELECT * FROM wines")
}

Fetching Methods

Throughout GRDB, you can always fetch cursors, arrays, or single values of any fetchable type (database row, simple value, or custom record):

try Row.fetchCursor(...) // A Cursor of Row
try Row.fetchAll(...)    // [Row]
try Row.fetchOne(...)    // Row?

  • fetchCursor returns a cursor over fetched values:

    let rows = try Row.fetchCursor(db, "SELECT ...") // A Cursor of Row

  • fetchAll returns an array:

    let players = try Player.fetchAll(db, "SELECT ...") // [Player]

  • fetchOne returns a single optional value, and consumes a single database row (if any).

    let count = try Int.fetchOne(db, "SELECT COUNT(*) ...") // Int?

Cursors

Whenever you consume several rows from the database, you can fetch a Cursor, or an Array.

The fetchAll() method returns a regular Swift array, that you iterate like all other arrays:

try dbQueue.inDatabase { db in
    // [Player]
    let players = try Player.fetchAll(db, "SELECT ...")
    for player in players {
        // use player
    }
}

Unlike arrays, cursors returned by fetchCursor() load their results step after step:

try dbQueue.inDatabase { db in
    // Cursor of Player
    let players = try Player.fetchCursor(db, "SELECT ...")
    while let player = try players.next() {
        // use player
    }
}

Both arrays and cursors can iterate over database results. How do you choose one or the other? Look at the differences:

  • Cursors can not be used on any thread: you must consume a cursor on the dispatch queue it was created in. Arrays may be consumed on any thread.
  • Cursors can be iterated only one time. Arrays can be iterated many times.
  • Cursors iterate database results in a lazy fashion, and don’t consume much memory. Arrays contain copies of database values, and may take a lot of memory when there are many fetched results.
  • Cursors are granted with direct access to SQLite, unlike arrays that have to take the time to copy database values. When you really care about performance, you may want to deal with cursors of raw rows at the lowest possible level: Row.fetchCursor(...).

  • Cursors require a little care:

    • Don’t modify the results during a cursor iteration:

      // Undefined behavior
while let player = try players.next() {
    try db.execute("DELETE ...")
}

    • Don’t turn a cursor of Row into an array. You would not get the distinct rows you expect. To get a array of rows, use Row.fetchAll(...). Generally speaking, make sure you copy a row whenever you extract it from a cursor for later use: row.copy().

If you don’t see, or don’t care about the difference, use arrays. If you care about memory and performance, use cursors when appropriate.

All GRDB cursors adopt the Cursor protocol, which looks a lot like standard lazy sequences of Swift. As such, cursors come with many convenience methods: contains, dropFirst, dropLast, drop(while:), enumerated, filter, first, flatMap, forEach, joined, joined(separator:), max, max(by:), min, min(by:), map, prefix, prefix(while:), reduce, reduce(into:), suffix:

// All URL hosts
let hosts = try URL
    .fetchCursor(db, "SELECT url FROM links")
    .map { url in url.host }

// Prints all Github links
try URL
    .fetchCursor(db, "SELECT url FROM links")
    .filter { url in url.host == "github.com" }
    .forEach { url in print(url) }

// Turn a cursor into an array:
let cursor = URL
    .fetchCursor(db, "SELECT url FROM links")
    .filter { url in url.host == "github.com" }
let githubURLs = try Array(cursor) // [URL]

// Turn a cursor into a set:
let cursor = URL
    .fetchCursor(db, "SELECT url FROM links")
    .flatMap { url in url.host }
let hosts = try Set(cursor) // Set<String>

Cursors are not Swift sequences, though. That’s because Swift sequences can’t handle iteration errors, when reading SQLite results may fail at any time. SQL functions may throw errors. On iOS, data protection may block access to the database file in the background. On MacOS, your application users may mess with the file system.

Row Queries

Fetching Rows

Fetch cursors of rows, arrays, or single rows (see fetching methods):

try dbQueue.inDatabase { db in
    try Row.fetchCursor(db, "SELECT ...", arguments: ...) // A Cursor of Row
    try Row.fetchAll(db, "SELECT ...", arguments: ...)    // [Row]
    try Row.fetchOne(db, "SELECT ...", arguments: ...)    // Row?

    let rows = try Row.fetchCursor(db, "SELECT * FROM wines")
    while let row = try rows.next() {
        let name: String = row["name"]
        let color: Color = row["color"]
        print(name, color)
    }
}

let rows = try dbQueue.inDatabase { db in
    try Row.fetchAll(db, "SELECT * FROM players")
}

Arguments are optional arrays or dictionaries that fill the positional ? and colon-prefixed keys like :name in the query:

let rows = try Row.fetchAll(db,
    "SELECT * FROM players WHERE name = ?",
    arguments: ["Arthur"])

let rows = try Row.fetchAll(db,
    "SELECT * FROM players WHERE name = :name",
    arguments: ["name": "Arthur"])

See Values for more information on supported arguments types (Bool, Int, String, Date, Swift enums, etc.), and StatementArguments for a detailed documentation of SQLite arguments.

Unlike row arrays that contain copies of the database rows, row cursors are close to the SQLite metal, and require a little care:

:point_up: Don’t turn a cursor of Row into an array. You would not get the distinct rows you expect. To get a array of rows, use Row.fetchAll(...). Generally speaking, make sure you copy a row whenever you extract it from a cursor for later use: row.copy().

Column Values

Read column values by index or column name:

let name: String = row[0]      // 0 is the leftmost column
let name: String = row["name"] // Leftmost matching column - lookup is case-insensitive
let name: String = row[Column("name")] // Using query interface's Column

Make sure to ask for an optional when the value may be NULL:

let name: String? = row["name"]

The row[] subscript returns the type you ask for. See Values for more information on supported value types:

let bookCount: Int     = row["bookCount"]
let bookCount64: Int64 = row["bookCount"]
let hasBooks: Bool     = row["bookCount"] // false when 0

let string: String     = row["date"]      // "2015-09-11 18:14:15.123"
let date: Date         = row["date"]      // Date
self.date = row["date"] // Depends on the type of the property.

You can also use the as type casting operator:

row[...] as Int
row[...] as Int?

:warning: Warning: avoid the as! and as? operators, because they misbehave in the context of type inference (see rdar://21676393):

if let int = row[...] as? Int { ... } // BAD - doesn't work
if let int = row[...] as Int? { ... } // GOOD

Generally speaking, you can extract the type you need, provided it can be converted from the underlying SQLite value:

  • Successful conversions include:

    • All numeric SQLite values to all numeric Swift types, and Bool (zero is the only false boolean).
    • Text SQLite values to Swift String.
    • Blob SQLite values to Foundation Data.

    See Values for more information on supported types (Bool, Int, String, Date, Swift enums, etc.)

  • NULL returns nil.

    let row = try Row.fetchOne(db, "SELECT NULL")!
row[0] as Int? // nil
row[0] as Int  // fatal error: could not convert NULL to Int.

    There is one exception, though: the DatabaseValue type:

    row[0] as DatabaseValue // DatabaseValue.null

  • Missing columns return nil.

    let row = try Row.fetchOne(db, "SELECT 'foo' AS foo")!
row["missing"] as String? // nil
row["missing"] as String  // fatal error: no such column: missing

    You can explicitly check for a column presence with the hasColumn method.

  • Invalid conversions throw a fatal error.

    let row = try Row.fetchOne(db, "SELECT 'Mom’s birthday'")!
row[0] as String // "Mom’s birthday"
row[0] as Date?  // fatal error: could not convert "Mom’s birthday" to Date.
row[0] as Date   // fatal error: could not convert "Mom’s birthday" to Date.

    This fatal error can be avoided: see Fatal Errors.

  • SQLite has a weak type system, and provides convenience conversions that can turn Blob to String, String to Int, etc.

    GRDB will sometimes let those conversions go through:

    let rows = try Row.fetchCursor(db, "SELECT '20 small cigars'")
while let row = try rows.next() {
    row[0] as Int   // 20
}

    Don’t freak out: those conversions did not prevent SQLite from becoming the immensely successful database engine you want to use. And GRDB adds safety checks described just above. You can also prevent those convenience conversions altogether by using the DatabaseValue type.

DatabaseValue

DatabaseValue is an intermediate type between SQLite and your values, which gives information about the raw value stored in the database.

You get DatabaseValue just like other value types:

let dbValue: DatabaseValue = row[0]
let dbValue: DatabaseValue = row["name"]

// Check for NULL:
dbValue.isNull // Bool

// The stored value:
dbValue.storage.value // Int64, Double, String, Data, or nil

// All the five storage classes supported by SQLite:
switch dbValue.storage {
case .null:                 print("NULL")
case .int64(let int64):     print("Int64: \(int64)")
case .double(let double):   print("Double: \(double)")
case .string(let string):   print("String: \(string)")
case .blob(let data):       print("Data: \(data)")
}

You can extract regular values (Bool, Int, String, Date, Swift enums, etc.) from DatabaseValue with the DatabaseValueConvertible.fromDatabaseValue() method:

let dbValue: DatabaseValue = row["bookCount"]
let bookCount   = Int.fromDatabaseValue(dbValue)   // Int?
let bookCount64 = Int64.fromDatabaseValue(dbValue) // Int64?
let hasBooks    = Bool.fromDatabaseValue(dbValue)  // Bool?, false when 0

let dbValue: DatabaseValue = row["date"]
let string = String.fromDatabaseValue(dbValue)     // "2015-09-11 18:14:15.123"
let date   = Date.fromDatabaseValue(dbValue)       // Date?

fromDatabaseValue returns nil for invalid conversions:

let row = try Row.fetchOne(db, "SELECT 'Mom’s birthday'")!
let dbValue: DatabaseValue = row[0]
let string = String.fromDatabaseValue(dbValue) // "Mom’s birthday"
let int    = Int.fromDatabaseValue(dbValue)    // nil
let date   = Date.fromDatabaseValue(dbValue)   // nil

This turns out useful when you process untrusted databases. Compare:

let date: Date? = row[0]  // fatal error: could not convert "Mom’s birthday" to Date.
let date = Date.fromDatabaseValue(row[0]) // nil

Rows as Dictionaries

Row adopts the standard Collection protocol, and can be seen as a dictionary of DatabaseValue:

// All the (columnName, dbValue) tuples, from left to right:
for (columnName, dbValue) in row {
    ...
}

You can build rows from dictionaries (standard Swift dictionaries and NSDictionary). See Values for more information on supported types:

let row: Row = ["name": "foo", "date": nil]
let row = Row(["name": "foo", "date": nil])
let row = Row(/* [AnyHashable: Any] */) // nil if invalid dictionary

Yet rows are not real dictionaries: they may contain duplicate columns:

let row = try Row.fetchOne(db, "SELECT 1 AS foo, 2 AS foo")!
row.columnNames    // ["foo", "foo"]
row.databaseValues // [1, 2]
row["foo"]         // 1 (leftmost matching column)
for (columnName, dbValue) in row { ... } // ("foo", 1), ("foo", 2)

When you build a dictionary from a row, you have to disambiguate identical columns, and choose how to present database values. For example:

  • A [String: DatabaseValue] dictionary that keeps leftmost value in case of duplicated column name:

    let dict = Dictionary(row, uniquingKeysWith: { (left, _) in left })

  • A [String: AnyObject] dictionary which keeps rightmost value in case of duplicated column name. This dictionary is identical to FMResultSet’s resultDictionary from FMDB. It contains NSNull values for null columns, and can be shared with Objective-C:

    let dict = Dictionary(
    row.map { (column, dbValue) in
        (column, dbValue.storage.value as AnyObject)
    },
    uniquingKeysWith: { (_, right) in right })

  • A [String: Any] dictionary that can feed, for example, JSONSerialization:

    let dict = Dictionary(
    row.map { (column, dbValue) in
        (column, dbValue.storage.value)
    },
    uniquingKeysWith: { (left, _) in left })

See the documentation of Dictionary.init(_:uniquingKeysWith:) for more information.

Value Queries

Instead of rows, you can directly fetch values. Like rows, fetch them as cursors, arrays, or single values (see fetching methods). Values are extracted from the leftmost column of the SQL queries:

try dbQueue.inDatabase { db in
    try Int.fetchCursor(db, "SELECT ...", arguments: ...) // A Cursor of Int
    try Int.fetchAll(db, "SELECT ...", arguments: ...)    // [Int]
    try Int.fetchOne(db, "SELECT ...", arguments: ...)    // Int?

    // When database may contain NULL:
    try Optional<Int>.fetchCursor(db, "SELECT ...", arguments: ...) // A Cursor of Int?
    try Optional<Int>.fetchAll(db, "SELECT ...", arguments: ...)    // [Int?]
}

let playerCount = try dbQueue.inDatabase { db in
    try Int.fetchOne(db, "SELECT COUNT(*) FROM players")!
}

fetchOne returns an optional value which is nil in two cases: either the SELECT statement yielded no row, or one row with a NULL value.

There are many supported value types (Bool, Int, String, Date, Swift enums, etc.). See Values for more information:

let count = try Int.fetchOne(db, "SELECT COUNT(*) FROM players")! // Int
let urls = try URL.fetchAll(db, "SELECT url FROM links")          // [URL]

Values

GRDB ships with built-in support for the following value types:

Values can be used as statement arguments:

let url: URL = ...
let verified: Bool = ...
try db.execute(
    "INSERT INTO links (url, verified) VALUES (?, ?)",
    arguments: [url, verified])

Values can be extracted from rows:

let rows = try Row.fetchCursor(db, "SELECT * FROM links")
while let row = try rows.next() {
    let url: URL = row["url"]
    let verified: Bool = row["verified"]
}

Values can be directly fetched:

let urls = try URL.fetchAll(db, "SELECT url FROM links")  // [URL]

Use values in Records:

class Link : Record {
    var url: URL
    var isVerified: Bool

    required init(row: Row) {
        url = row["url"]
        isVerified = row["verified"]
        super.init(row: row)
    }

    override func encode(to container: inout PersistenceContainer) {
        container["url"] = url
        container["verified"] = isVerified
    }
}

Use values in the query interface:

let url: URL = ...
let link = try Link.filter(urlColumn == url).fetchOne(db)

Data (and Memory Savings)

Data suits the BLOB SQLite columns. It can be stored and fetched from the database just like other values:

let rows = try Row.fetchCursor(db, "SELECT data, ...")
while let row = try rows.next() {
    let data: Data = row["data"]
}

At each step of the request iteration, the row[] subscript creates two copies of the database bytes: one fetched by SQLite, and another, stored in the Swift Data value.

You have the opportunity to save memory by not copying the data fetched by SQLite:

while let row = try rows.next() {
    let data = row.dataNoCopy(named: "data") // Data?
}

The non-copied data does not live longer than the iteration step: make sure that you do not use it past this point.

Date and DateComponents

Date and DateComponents can be stored and fetched from the database.

Here is the support provided by GRDB for the various date formats supported by SQLite:

SQLite format Date DateComponents
YYYY-MM-DD Read ¹ Read/Write
YYYY-MM-DD HH:MM Read ¹ Read/Write
YYYY-MM-DD HH:MM:SS Read ¹ Read/Write
YYYY-MM-DD HH:MM:SS.SSS Read/Write ¹ Read/Write
YYYY-MM-DD*T*HH:MM Read ¹ Read
YYYY-MM-DD*T*HH:MM:SS Read ¹ Read
YYYY-MM-DD*T*HH:MM:SS.SSS Read ¹ Read
HH:MM Read/Write
HH:MM:SS Read/Write
HH:MM:SS.SSS Read/Write
Timestamps since unix epoch Read ²
now

¹ Dates are stored and read in the UTC time zone. Missing components are assumed to be zero.

² GRDB 2.0 interprets numerical values as timestamps that fuel Date(timeIntervalSince1970:). Previous GRDB versions used to interpret numbers as julian days. GRDB 2.0 still supports julian days, with the Date(julianDay:) initializer.

Date

Date can be stored and fetched from the database just like other values:

try db.execute(
    "INSERT INTO players (creationDate, ...) VALUES (?, ...)",
    arguments: [Date(), ...])

let creationDate: Date = row["creationDate"]

Dates are stored using the format YYYY-MM-DD HH:MM:SS.SSS in the UTC time zone. It is precise to the millisecond.

:point_up: Note: this format was chosen because it is the only format that is:

  • Comparable (ORDER BY date works)
  • Comparable with the SQLite keyword CURRENT_TIMESTAMP (WHERE date > CURRENT_TIMESTAMP works)
  • Able to feed SQLite date & time functions
  • Precise enough

Yet this format may not fit your needs. For example, you may want to store dates as timestamps. In this case, store and load Doubles instead of Date, and perform the required conversions.

DateComponents

DateComponents is indirectly supported, through the DatabaseDateComponents helper type.

DatabaseDateComponents reads date components from all date formats supported by SQLite, and stores them in the format of your choice, from HH:MM to YYYY-MM-DD HH:MM:SS.SSS.

DatabaseDateComponents can be stored and fetched from the database just like other values:

let components = DateComponents()
components.year = 1973
components.month = 9
components.day = 18

// Store "1973-09-18"
let dbComponents = DatabaseDateComponents(components, format: .YMD)
try db.execute(
    "INSERT INTO players (birthDate, ...) VALUES (?, ...)",
    arguments: [dbComponents, ...])

// Read "1973-09-18"
let row = try Row.fetchOne(db, "SELECT birthDate ...")!
let dbComponents: DatabaseDateComponents = row["birthDate"]
dbComponents.format         // .YMD (the actual format found in the database)
dbComponents.dateComponents // DateComponents

NSNumber and NSDecimalNumber

NSNumber can be stored and fetched from the database just like other values. Floating point NSNumbers are stored as Double. Integer and boolean, as Int64. Integers that don’t fit Int64 won’t be stored: you’ll get a fatal error instead. Be cautious when an NSNumber contains an UInt64, for example.

NSDecimalNumber deserves a longer discussion:

SQLite has no support for decimal numbers. Given the table below, SQLite will actually store integers or doubles:

CREATE TABLE transfers (
    amount DECIMAL(10,5) -- will store integer or double, actually
)

This means that computations will not be exact:

try db.execute("INSERT INTO transfers (amount) VALUES (0.1)")
try db.execute("INSERT INTO transfers (amount) VALUES (0.2)")
let sum = try NSDecimalNumber.fetchOne(db, "SELECT SUM(amount) FROM transfers")!

// Yikes! 0.3000000000000000512
print(sum)

Don’t blame SQLite or GRDB, and instead store your decimal numbers differently.

A classic technique is to store integers instead, since SQLite performs exact computations of integers. For example, don’t store Euros, but store cents instead:

// Store
let amount = NSDecimalNumber(string: "0.1")                       // 0.1
let integerAmount = amount.multiplying(byPowerOf10: 2).int64Value // 100
try db.execute("INSERT INTO transfers (amount) VALUES (?)", arguments: [integerAmount])

// Read
let integerAmount = try Int64.fetchOne(db, "SELECT SUM(amount) FROM transfers")!    // 100
let amount = NSDecimalNumber(value: integerAmount).multiplying(byPowerOf10: -2) // 0.1

UUID

UUID can be stored and fetched from the database just like other values. GRDB stores uuids as 16-bytes data blobs.

Swift Enums

Swift enums and generally all types that adopt the RawRepresentable protocol can be stored and fetched from the database just like their raw values:

enum Color : Int {
    case red, white, rose
}

enum Grape : String {
    case chardonnay, merlot, riesling
}

// Declare empty DatabaseValueConvertible adoption
extension Color : DatabaseValueConvertible { }
extension Grape : DatabaseValueConvertible { }

// Store
try db.execute(
    "INSERT INTO wines (grape, color) VALUES (?, ?)",
    arguments: [Grape.merlot, Color.red])

// Read
let rows = try Row.fetchCursor(db, "SELECT * FROM wines")
while let row = try rows.next() {
    let grape: Grape = row["grape"]
    let color: Color = row["color"]
}

When a database value does not match any enum case, you get a fatal error. This fatal error can be avoided with the DatabaseValueConvertible.fromDatabaseValue() method:

let row = try Row.fetchOne(db, "SELECT 'syrah'")!

row[0] as String  // "syrah"
row[0] as Grape?  // fatal error: could not convert "syrah" to Grape.
row[0] as Grape   // fatal error: could not convert "syrah" to Grape.
Grape.fromDatabaseValue(row[0])  // nil

Transactions and Savepoints

The DatabaseQueue.inTransaction() and DatabasePool.writeInTransaction() methods open an SQLite transaction and run their closure argument in a protected dispatch queue. They block the current thread until your database statements are executed:

try dbQueue.inTransaction { db in
    let wine = Wine(color: .red, name: "Pomerol")
    try wine.insert(db)
    return .commit
}

If an error is thrown within the transaction body, the transaction is rollbacked and the error is rethrown by the inTransaction method. If you return .rollback from your closure, the transaction is also rollbacked, but no error is thrown.

If you want to insert a transaction between other database statements, you can use the Database.inTransaction() function, or even raw SQL statements:

try dbQueue.inDatabase { db in  // or dbPool.write { db in
    ...
    try db.inTransaction {
        ...
        return .commit
    }
    ...
    try db.beginTransaction()
    ...
    try db.commit()
    ...
    try db.execute("BEGIN TRANSACTION")
    ...
    try db.execute("COMMIT")
}

You can ask a database if a transaction is currently opened:

func myCriticalMethod(_ db: Database) throws {
    precondition(db.isInsideTransaction, "This method requires a transaction")
    try ...
}

Yet, you have a better option than checking for transactions: critical sections of your application should use savepoints, described below:

func myCriticalMethod(_ db: Database) throws {
    try db.inSavepoint {
        // Here the database is guaranteed to be inside a transaction.
        try ...
    }
}

Savepoints

Statements grouped in a savepoint can be rollbacked without invalidating a whole transaction:

try dbQueue.inTransaction { db in
    try db.inSavepoint { 
        try db.execute("DELETE ...")
        try db.execute("INSERT ...") // need to rollback the delete above if this fails
        return .commit
    }

    // Other savepoints, etc...
    return .commit
}

If an error is thrown within the savepoint body, the savepoint is rollbacked and the error is rethrown by the inSavepoint method. If you return .rollback from your closure, the body is also rollbacked, but no error is thrown.

Unlike transactions, savepoints can be nested. They implicitly open a transaction if no one was opened when the savepoint begins. As such, they behave just like nested transactions. Yet the database changes are only committed to disk when the outermost savepoint is committed:

try dbQueue.inDatabase { db in
    try db.inSavepoint {
        ...
        try db.inSavepoint {
            ...
            return .commit
        }
        ...
        return .commit  // writes changes to disk
    }
}

SQLite savepoints are more than nested transactions, though. For advanced savepoints uses, use SQL queries.

Transaction Kinds

SQLite supports three kinds of transactions: deferred (the default), immediate, and exclusive.

The transaction kind can be changed in the database configuration, or for each transaction:

// Set the default transaction kind to IMMEDIATE:
var config = Configuration()
config.defaultTransactionKind = .immediate
let dbQueue = try DatabaseQueue(path: "...", configuration: config)

// BEGIN IMMEDIATE TRANSACTION ...
dbQueue.inTransaction { db in ... }

// BEGIN EXCLUSIVE TRANSACTION ...
dbQueue.inTransaction(.exclusive) { db in ... }

Custom Value Types

Conversion to and from the database is based on the DatabaseValueConvertible protocol:

protocol DatabaseValueConvertible {
    /// Returns a value that can be stored in the database.
    var databaseValue: DatabaseValue { get }

    /// Returns a value initialized from dbValue, if possible.
    static func fromDatabaseValue(_ dbValue: DatabaseValue) -> Self?
}

All types that adopt this protocol can be used like all other values (Bool, Int, String, Date, Swift enums, etc.)

The databaseValue property returns DatabaseValue, a type that wraps the five values supported by SQLite: NULL, Int64, Double, String and Data. Since DatabaseValue has no public initializer, use DatabaseValue.null, or another type that already adopts the protocol: 1.databaseValue, "foo".databaseValue, etc. Conversion to DatabaseValue must not fail.

The fromDatabaseValue() factory method returns an instance of your custom type if the database value contains a suitable value. If the database value does not contain a suitable value, such as foo for Date, fromDatabaseValue must return nil (GRDB will interpret this nil result as a conversion error, and react accordingly).

Prepared Statements

Prepared Statements let you prepare an SQL query and execute it later, several times if you need, with different arguments.

There are two kinds of prepared statements: select statements, and update statements:

try dbQueue.inDatabase { db in
    let updateSQL = "INSERT INTO players (name, score) VALUES (:name, :score)"
    let updateStatement = try db.makeUpdateStatement(updateSQL)

    let selectSQL = "SELECT * FROM players WHERE name = ?"
    let selectStatement = try db.makeSelectStatement(selectSQL)
}

The ? and colon-prefixed keys like :name in the SQL query are the statement arguments. You set them with arrays or dictionaries (arguments are actually of type StatementArguments, which happens to adopt the ExpressibleByArrayLiteral and ExpressibleByDictionaryLiteral protocols).

updateStatement.arguments = ["name": "Arthur", "score": 1000]
selectStatement.arguments = ["Arthur"]

After arguments are set, you can execute the prepared statement:

try updateStatement.execute()

Select statements can be used wherever a raw SQL query string would fit (see fetch queries):

let rows = try Row.fetchCursor(selectStatement)    // A Cursor of Row
let players = try Player.fetchAll(selectStatement) // [Player]
let player = try Player.fetchOne(selectStatement)  // Player?

You can set the arguments at the moment of the statement execution:

try updateStatement.execute(arguments: ["name": "Arthur", "score": 1000])
let player = try Player.fetchOne(selectStatement, arguments: ["Arthur"])

:point_up: Note: it is a programmer error to reuse a prepared statement that has failed: GRDB may crash if you do so.

See row queries, value queries, and Records for more information.

Prepared Statements Cache

When the same query will be used several times in the lifetime of your application, you may feel a natural desire to cache prepared statements.

Don’t cache statements yourself.

:point_up: Note: This is because you don’t have the necessary tools. Statements are tied to specific SQLite connections and dispatch queues which you don’t manage yourself, especially when you use database pools. A change in the database schema may, or may not invalidate a statement. On systems earlier than iOS 8.2 and OSX 10.10 that don’t have the sqlite3_close_v2 function, SQLite connections won’t close properly if statements have been kept alive.

Instead, use the cachedUpdateStatement and cachedSelectStatement methods. GRDB does all the hard caching and memory management stuff for you:

let updateStatement = try db.cachedUpdateStatement(sql)
let selectStatement = try db.cachedSelectStatement(sql)

Should a cached prepared statement throw an error, don’t reuse it (it is a programmer error). Instead, reload it from the cache.

Custom SQL Functions and Aggregates

SQLite lets you define SQL functions and aggregates.

A custom SQL function or aggregate extends SQLite:

SELECT reverse(name) FROM players;   -- custom function
SELECT maxLength(name) FROM players; -- custom aggregate

Custom SQL Functions

let reverse = DatabaseFunction("reverse", argumentCount: 1, pure: true) { (values: [DatabaseValue]) in
    // Extract string value, if any...
    guard let string = String.fromDatabaseValue(values[0]) else {
        return nil
    }
    // ... and return reversed string:
    return String(string.characters.reversed())
}
dbQueue.add(function: reverse)   // Or dbPool.add(function: ...)

try dbQueue.inDatabase { db in
    // "oof"
    try String.fetchOne(db, "SELECT reverse('foo')")!
}

The function argument takes an array of DatabaseValue, and returns any valid value (Bool, Int, String, Date, Swift enums, etc.) The number of database values is guaranteed to be argumentCount.

SQLite has the opportunity to perform additional optimizations when functions are pure, which means that their result only depends on their arguments. So make sure to set the pure argument to true when possible.

Functions can take a variable number of arguments:

When you don’t provide any explicit argumentCount, the function can take any number of arguments:

let averageOf = DatabaseFunction("averageOf", pure: true) { (values: [DatabaseValue]) in
    let doubles = values.flatMap { Double.fromDatabaseValue($0) }
    return doubles.reduce(0, +) / Double(doubles.count)
}
dbQueue.add(function: averageOf)

try dbQueue.inDatabase { db in
    // 2.0
    try Double.fetchOne(db, "SELECT averageOf(1, 2, 3)")!
}

Functions can throw:

let sqrt = DatabaseFunction("sqrt", argumentCount: 1, pure: true) { (values: [DatabaseValue]) in
    guard let double = Double.fromDatabaseValue(values[0]) else {
        return nil
    }
    guard double >= 0 else {
        throw DatabaseError(message: "invalid negative number")
    }
    return sqrt(double)
}
dbQueue.add(function: sqrt)

// SQLite error 1 with statement `SELECT sqrt(-1)`: invalid negative number
try dbQueue.inDatabase { db in
    try Double.fetchOne(db, "SELECT sqrt(-1)")!
}

Use custom functions in the query interface:

// SELECT reverseString("name") FROM players
Player.select(reverseString.apply(nameColumn))

GRDB ships with built-in SQL functions that perform unicode-aware string transformations. See Unicode.

Custom Aggregates

Before registering a custom aggregate, you need to define a type that adopts the DatabaseAggregate protocol:

protocol DatabaseAggregate {
    // Initializes an aggregate
    init()

    // Called at each step of the aggregation
    mutating func step(_ dbValues: [DatabaseValue]) throws

    // Returns the final result
    func finalize() throws -> DatabaseValueConvertible?
}

For example:

struct MaxLength : DatabaseAggregate {
    var maxLength: Int = 0

    mutating func step(_ dbValues: [DatabaseValue]) {
        // At each step, extract string value, if any...
        guard let string = String.fromDatabaseValue(dbValues[0]) else {
            return
        }
        // ... and update the result
        let length = string.characters.count
        if length > maxLength {
            maxLength = length
        }
    }

    func finalize() -> DatabaseValueConvertible? {
        return maxLength
    }
}

let maxLength = DatabaseFunction(
    "maxLength",
    argumentCount: 1,
    pure: true,
    aggregate: MaxLength.self)

dbQueue.add(function: maxLength)   // Or dbPool.add(function: ...)

try dbQueue.inDatabase { db in
    // Some Int
    try Int.fetchOne(db, "SELECT maxLength(name) FROM players")!
}

The step method of the aggregate takes an array of DatabaseValue. This array contains as many values as the argumentCount parameter (or any number of values, when argumentCount is omitted).

The finalize method of the aggregate returns the final aggregated value (Bool, Int, String, Date, Swift enums, etc.).

SQLite has the opportunity to perform additional optimizations when aggregates are pure, which means that their result only depends on their inputs. So make sure to set the pure argument to true when possible.

Use custom aggregates in the query interface:

// SELECT maxLength("name") FROM players
Player.select(maxLength.apply(nameColumn))
    .asRequest(of: Int.self)
    .fetchOne(db) // Int?

Database Schema Introspection

SQLite provides database schema introspection tools, such as the sqlite_master table, and the pragma table_info:

try db.create(table: "players") { t in
    t.column("id", .integer).primaryKey()
    t.column("name", .text)
}

// <Row type:"table" name:"players" tbl_name:"players" rootpage:2
//      sql:"CREATE TABLE players(id INTEGER PRIMARY KEY, name TEXT)">
for row in try Row.fetchAll(db, "SELECT * FROM sqlite_master") {
    print(row)
}

// <Row cid:0 name:"id" type:"INTEGER" notnull:0 dflt_value:NULL pk:1>
// <Row cid:1 name:"name" type:"TEXT" notnull:0 dflt_value:NULL pk:0>
for row in try Row.fetchAll(db, "PRAGMA table_info('players')") {
    print(row)
}

GRDB provides high-level methods as well:

try db.tableExists("players")     // Bool, true if the table exists
try db.columns(in: "players")     // [ColumnInfo], the columns in the table
try db.indexes(on: "players")     // [IndexInfo], the indexes defined on the table
try db.foreignKeys(on: "players") // [ForeignKeyInfo], the foreign keys defined on the table
try db.primaryKey("players")      // PrimaryKeyInfo
try db.table("players", hasUniqueKey: ["email"]) // Bool, true if column(s) is a unique key

Row Adapters

Row adapters let you present database rows in the way expected by the row consumers.

They basically help two incompatible row interfaces to work together. For example, a row consumer expects a column named consumed, but the produced row has a column named produced.

In this case, the ColumnMapping row adapter comes in handy:

// Fetch a 'produced' column, and consume a 'consumed' column:
let adapter = ColumnMapping(["consumed": "produced"])
let row = try Row.fetchOne(db, "SELECT 'Hello' AS produced", adapter: adapter)!
row["consumed"] // "Hello"
row["produced"] // nil

Row adapters are values that adopt the RowAdapter protocol. You can implement your own custom adapters (:fire: EXPERIMENTAL), or use one of the four built-in adapters, described below.

To see how row adapters can be used, see Joined Queries Support.

ColumnMapping

ColumnMapping renames columns. Build one with a dictionary whose keys are adapted column names, and values the column names in the raw row:

// <Row newName:"Hello">
let adapter = ColumnMapping(["newName": "oldName"])
let row = try Row.fetchOne(db, "SELECT 'Hello' AS oldName", adapter: adapter)!

SuffixRowAdapter

SuffixRowAdapter hides the first columns in a row:

// <Row b:1 c:2>
let adapter = SuffixRowAdapter(fromIndex: 1)
let row = try Row.fetchOne(db, "SELECT 0 AS a, 1 AS b, 2 AS c", adapter: adapter)!

RangeRowAdapter

RangeRowAdapter only exposes a range of columns.

// <Row b:1>
let adapter = RangeRowAdapter(1..<2)
let row = try Row.fetchOne(db, "SELECT 0 AS a, 1 AS b, 2 AS c", adapter: adapter)!

EmptyRowAdapter

EmptyRowAdapter hides all rows.

let adapter = EmptyRowAdapter()
let row = try Row.fetchOne(db, "SELECT 0 AS a, 1 AS b, 2 AS c", adapter: adapter)!
row.isEmpty // true

This limit adapter may turn out useful in some narrow use cases. You’ll be happy to find it when you need it.

ScopeAdapter

ScopeAdapter defines row scopes:

let adapter = ScopeAdapter([
    "left": RangeRowAdapter(0..<2),
    "right": RangeRowAdapter(2..<4)])
let row = try Row.fetchOne(db, "SELECT 0 AS a, 1 AS b, 2 AS c, 3 AS d", adapter: adapter)!

ScopeAdapter does not change the columns and values of the fetched row. Instead, it defines scopes, which you access with the Row.scoped(on:) method. This method returns an optional Row, which is nil if the scope is missing.

row                       // <Row a:0 b:1 c:2 d:3>
row.scoped(on: "left")    // <Row a:0 b:1>
row.scoped(on: "right")   // <Row c:2 d:3>
row.scoped(on: "missing") // nil

Scopes can be nested:

let adapter = ScopeAdapter([
    "left": ScopeAdapter([
        "left": RangeRowAdapter(0..<1),
        "right": RangeRowAdapter(1..<2)]),
    "right": ScopeAdapter([
        "left": RangeRowAdapter(2..<3),
        "right": RangeRowAdapter(3..<4)])
    ])
let row = try Row.fetchOne(db, "SELECT 0 AS a, 1 AS b, 2 AS c, 3 AS d", adapter: adapter)!

let leftRow = row.scoped(on: "left")!
leftRow.scoped(on: "left")  // <Row a:0>
leftRow.scoped(on: "right") // <Row b:1>

let rightRow = row.scoped(on: "right")!
rightRow.scoped(on: "left")  // <Row c:2>
rightRow.scoped(on: "right") // <Row d:3>

Any adapter can be extended with scopes:

let baseAdapter = RangeRowAdapter(0..<2)
let adapter = ScopeAdapter(base: baseAdapter, scopes: [
    "remainder": SuffixRowAdapter(fromIndex: 2)])
let row = try Row.fetchOne(db, "SELECT 0 AS a, 1 AS b, 2 AS c, 3 AS d", adapter: adapter)!

row // <Row a:0 b:1>
row.scoped(on: "remainder") // <Row c:2 d:3>

Raw SQLite Pointers

If not all SQLite APIs are exposed in GRDB, you can still use the SQLite C Interface and call SQLite C functions.

Those functions are embedded right into the GRDBCustom and GRCBCipher modules. For the regular GRDB framework: you’ll need to import SQLite3, or CSQLite, depending on whether you use the Swift Package Manager or not:

#if SWIFT_PACKAGE
    import CSQLite // For Swift Package Manager
#else
    import SQLite3 // Otherwise
#endif

let sqliteVersion = String(cString: sqlite3_libversion())

Raw pointers to database connections and statements are available through the Database.sqliteConnection and Statement.sqliteStatement properties:

try dbQueue.inDatabase { db in
    // The raw pointer to a database connection:
    let sqliteConnection = db.sqliteConnection

    // The raw pointer to a statement:
    let statement = try db.makeSelectStatement("SELECT ...")
    let sqliteStatement = statement.sqliteStatement
}

:point_up: Notes

  • Those pointers are owned by GRDB: don’t close connections or finalize statements created by GRDB.
  • GRDB opens SQLite connections in the [multi-thread mode](https://www.sqlite.org/threadsafe.html), which (oddly) means that they are not thread-safe. Make sure you touch raw databases and statements inside their dedicated dispatch queues.
  • Use the raw SQLite C Interface at your own risk. GRDB won’t prevent you from shooting yourself in the foot.

Before jumping in the low-level wagon, here is the list of all SQLite APIs used by GRDB:

Records

On top of the SQLite API, GRDB provides protocols and a class that help manipulating database rows as regular objects named records:

try dbQueue.inDatabase { db in
    if let place = try Place.fetchOne(db, key: 1) {
        place.isFavorite = true
        try place.update(db)
    }
}

Of course, you need to open a database connection, and create a database table first.

Your custom structs and classes can adopt each protocol individually, and opt in to focused sets of features. Or you can subclass the Record class, and get the full toolkit in one go: fetching methods, persistence methods, and changes tracking. See the list of record methods for an overview.

:point_up: Note: if you are familiar with Core Data’s NSManagedObject or Realm’s Object, you may experience a cultural shock: GRDB records are not uniqued, and do not auto-update. This is both a purpose, and a consequence of protocol-oriented programming. You should read How to build an iOS application with SQLite and GRDB.swift for a general introduction.

Overview

Protocols and the Record class

Inserting Records

To insert a record in the database, subclass the Record class or adopt the Persistable protocol, and call the insert method:

class Player : Record { ... }

let player = Player(name: "Arthur", email: "arthur@example.com")
try player.insert(db)

Fetching Records

Record subclasses and types that adopt the RowConvertible protocol can be fetched from the database:

class Player : Record { ... }
let players = try Player.fetchAll(db, "SELECT ...", arguments: ...) // [Player]

Add the TableMapping protocol and you can stop writing SQL:

let spain = try Country.fetchOne(db, key: "ES") // Country?
let players = try Player                        // [Player]
    .filter(Column("email") != nil)
    .order(Column("name"))
    .fetchAll(db)

See fetching methods, and the query interface.

Updating Records

Record subclasses and types that adopt the Persistable protocol can be updated in the database:

let player = try Player.fetchOne(db, key: 1)!
player.name = "Arthur"
try player.update(db)

Records can track their changes, so that you can avoid useless updates:

let player = try Player.fetchOne(db, key: 1)!
player.name = "Arthur"
if player.hasDatabaseChanges {
    try player.update(db)
}

For batch updates, execute an SQL query:

try db.execute("UPDATE players SET synchronized = 1")

Deleting Records

Record subclasses and types that adopt the Persistable protocol can be deleted from the database:

let player = try Player.fetchOne(db, key: 1)!
try player.delete(db)

Such records can also delete according to primary key or any unique index:

try Player.deleteOne(db, key: 1)
try Player.deleteOne(db, key: ["email": "arthur@example.com"])
try Country.deleteAll(db, keys: ["FR", "US"])

For batch deletes, see the query interface:

try Player.filter(emailColumn == nil).deleteAll(db)

Counting Records

Record subclasses and types that adopt the TableMapping protocol can be counted:

let playerWithEmailCount = try Player.filter(emailColumn != nil).fetchCount(db)  // Int

Details follow:

Record Protocols Overview

GRDB ships with three record protocols. Your own types will adopt one or several of them, according to the abilities you want to extend your types with.

  • RowConvertible is able to read: it grants the ability to efficiently decode raw database row.

    Imagine you want to load places from the places database table.

    One way to do it is to load raw database rows:

    func fetchPlaceRows(_ db: Database) throws -> [Row] {
    return try Row.fetchAll(db, "SELECT * FROM places")
}

    The problem is that raw rows are not easy to deal with, and you may prefer using a proper Place type:

    // Dedicated model
struct Place { ... }
func fetchPlaces(_ db: Database) throws -> [Place] {
    let rows = try Row.fetchAll(db, "SELECT * FROM places")
    return rows.map { row in
        Place(
            id: row["id"],
            title: row["title"],
            coordinate: CLLocationCoordinate2D(
                latitude: row["latitude"],
                longitude: row["longitude"]))
        )
    }
}

    This code is verbose, and so you define an init(row:) initializer:

    // Row initializer
struct Place {
    init(row: Row) {
        id = row["id"]
        ...
    }
}
func fetchPlaces(_ db: Database) throws -> [Place] {
    let rows = try Row.fetchAll(db, "SELECT * FROM places")
    return rows.map { Place(row: $0) }
}

    Now you notice that this code may use a lot of memory when you have many rows: a full array of database rows is created in order to build an array of places. Furthermore, rows that have been copied from the database have lost the ability to directly load values from SQLite: that’s inefficient. You thus use a database cursor, which is both lazy and efficient:

    // Cursor for efficiency
func fetchPlaces(_ db: Database) throws -> [Place] {
    let rowCursor = try Row.fetchCursor(db, "SELECT * FROM places")
    let placeCursor = rowCursor.map { Place(row: $0) }
    return try Array(placeCursor)
}

    That’s better. And that’s what RowConvertible does, with a little performance bonus, and in a single line:

    struct Place : RowConvertible {
    init(row: Row) { ... }
}
func fetchPlaces(_ db: Database) throws -> [Place] {
    return try Place.fetchAll(db, "SELECT * FROM places")
}

    RowConvertible is not able to build SQL requests, though. For that, you also need TableMapping:

  • TableMapping is able to build requests without SQL:

    struct Place : TableMapping { ... }
// SELECT * FROM places ORDER BY title
let request = Place.order(Column("title"))

    When a type adopts both TableMapping and RowConvertible, it can load from those requests:

    struct Place : TableMapping, RowConvertible { ... }
try dbQueue.inDatabase { db in
    let places = try Place.order(Column("title")).fetchAll(db)
    let paris = try Place.fetchOne(key: 1)
}

  • Persistable is able to write: it can create, update, and delete rows in the database:

    struct Place : Persistable { ... }
try dbQueue.inDatabase { db in
    try Place.delete(db, key: 1)
    try Place(...).insert(db)
}

RowConvertible Protocol

The RowConvertible protocol grants fetching methods to any type that can be built from a database row:

protocol RowConvertible {
    /// Row initializer
    init(row: Row)
}

To use RowConvertible, subclass the Record class, or adopt it explicitely. For example:

struct Place {
    var id: Int64?
    var title: String
    var coordinate: CLLocationCoordinate2D
}

extension Place : RowConvertible {
    init(row: Row) {
        id = row["id"]
        title = row["title"]
        coordinate = CLLocationCoordinate2D(
            latitude: row["latitude"],
            longitude: row["longitude"])
    }
}

Rows also accept keys of type Column:

extension Place : RowConvertible {
    enum Columns {
        static let id = Column("id")
        static let title = Column("title")
        static let latitude = Column("latitude")
        static let longitude = Column("longitude")
    }

    init(row: Row) {
        id = row[Columns.id]
        title = row[Columns.title]
        coordinate = CLLocationCoordinate2D(
            latitude: row[Columns.latitude],
            longitude: row[Columns.longitude])
    }
}

See column values for more information about the row[] subscript.

:point_up: Note: for performance reasons, the same row argument to init(row:) is reused during the iteration of a fetch query. If you want to keep the row for later use, make sure to store a copy: self.row = row.copy().

:bulb: Tip: the init(row:) initializer can be automatically generated when your type adopts the standard Decodable protocol. See Codable Records for more information.

RowConvertible allows adopting types to be fetched from SQL queries:

try Place.fetchCursor(db, "SELECT ...", arguments:...) // A Cursor of Place
try Place.fetchAll(db, "SELECT ...", arguments:...)    // [Place]
try Place.fetchOne(db, "SELECT ...", arguments:...)    // Place?

See fetching methods for information about the fetchCursor, fetchAll and fetchOne methods. See StatementArguments for more information about the query arguments.

TableMapping Protocol

Adopt the TableMapping protocol on top of RowConvertible, and you are granted with the full query interface.

protocol TableMapping {
    static var databaseTableName: String { get }
    static var databaseSelection: [SQLSelectable] { get }
}

The databaseTableName type property is the name of a database table. databaseSelection is optional, and documented in the Columns Selected by a Request chapter.

To use TableMapping, subclass the Record class, or adopt it explicitely. For example:

extension Place : TableMapping {
    static let databaseTableName = "places"
}

Adopting types can be fetched without SQL, using the query interface:

// SELECT * FROM places WHERE name = 'Paris'
let paris = try Place.filter(nameColumn == "Paris").fetchOne(db)

TableMapping can also fetch records by primary key:

try Player.fetchOne(db, key: 1)              // Player?
try Player.fetchAll(db, keys: [1, 2, 3])     // [Player]

try Country.fetchOne(db, key: "FR")          // Country?
try Country.fetchAll(db, keys: ["FR", "US"]) // [Country]

When the table has no explicit primary key, GRDB uses the hidden rowid column:

// SELECT * FROM documents WHERE rowid = 1
try Document.fetchOne(db, key: 1)            // Document?

For multiple-column primary keys and unique keys defined by unique indexes, provide a dictionary:

// SELECT * FROM citizenships WHERE playerID = 1 AND countryISOCode = 'FR'
try Citizenship.fetchOne(db, key: ["playerID": 1, "countryISOCode": "FR"]) // Citizenship?

Persistable Protocol

GRDB provides two protocols that let adopting types create, update, and delete rows in the database:

protocol MutablePersistable : TableMapping {
    /// The name of the database table (from TableMapping)
    static var databaseTableName: String { get }

    /// Defines the values persisted in the database
    func encode(to container: inout PersistenceContainer)

    /// Optional method that lets your adopting type store its rowID upon
    /// successful insertion. Don't call it directly: it is called for you.
    mutating func didInsert(with rowID: Int64, for column: String?)
}

protocol Persistable : MutablePersistable {
    /// Non-mutating version of the optional didInsert(with:for:)
    func didInsert(with rowID: Int64, for column: String?)
}

Yes, two protocols instead of one. Both grant exactly the same advantages. Here is how you pick one or the other:

  • If your type is a struct that mutates on insertion, choose MutablePersistable.

    For example, your table has an INTEGER PRIMARY KEY and you want to store the inserted id on successful insertion. Or your table has a UUID primary key, and you want to automatically generate one on insertion.

  • Otherwise, stick with Persistable. Particularly if your type is a class.

The encode(to:) method defines which values (Bool, Int, String, Date, Swift enums, etc.) are assigned to database columns.

:bulb: Tip: encode(to:) can be automatically generated when your type adopts the standard Encodable protocol. See Codable Records for more information.

The optional didInsert method lets the adopting type store its rowID after successful insertion. If your table has an INTEGER PRIMARY KEY column, you are likely to define this method. Otherwise, you can safely ignore it. It is called from a protected dispatch queue, and serialized with all database updates.

To use those protocols, subclass the Record class, or adopt one of them explicitely. For example:

extension Place : MutablePersistable {

    /// The values persisted in the database
    func encode(to container: inout PersistenceContainer) {
        container["id"] = id
        container["title"] = title
        container["latitude"] = coordinate.latitude
        container["longitude"] = coordinate.longitude
    }

    // Update id upon successful insertion:
    mutating func didInsert(with rowID: Int64, for column: String?) {
        id = rowID
    }
}

var paris = Place(
    id: nil,
    title: "Paris",
    coordinate: CLLocationCoordinate2D(latitude: 48.8534100, longitude: 2.3488000))

try paris.insert(db)
paris.id   // some value

Persistence containers also accept keys of type Column:

extension Place : MutablePersistable {
    enum Columns {
        static let id = Column("id")
        static let title = Column("title")
        static let latitude = Column("latitude")
        static let longitude = Column("longitude")
    }

    func encode(to container: inout PersistenceContainer) {
        container[Columns.id] = id
        container[Columns.title] = title
        container[Columns.latitude] = coordinate.latitude
        container[Columns.longitude] = coordinate.longitude
    }
}

Persistence Methods

Record subclasses and types that adopt Persistable are given default implementations for methods that insert, update, and delete:

// Instance methods
try place.save(db)                     // Inserts or updates
try place.insert(db)                   // INSERT
try place.update(db)                   // UPDATE
try place.update(db, columns: ...)     // UPDATE
try place.updateChanges(db, from: ...) // Maybe UPDATE
try place.updateChanges(db)            // Maybe UPDATE (Record class only)
try place.delete(db)                   // DELETE
place.exists(db)

// Type methods
Place.deleteAll(db)                    // DELETE
Place.deleteAll(db, keys:...)          // DELETE
Place.deleteOne(db, key:...)           // DELETE

  • insert, update, save and delete can throw a DatabaseError.

  • update and updateChanges can also throw a PersistenceError, should the update fail because there is no matching row in the database.

    When saving an object that may or may not already exist in the database, prefer the save method:

  • save makes sure your values are stored in the database.

    It performs an UPDATE if the record has a non-null primary key, and then, if no row was modified, an INSERT. It directly perfoms an INSERT if the record has no primary key, or a null primary key.

    Despite the fact that it may execute two SQL statements, save behaves as an atomic operation: GRDB won’t allow any concurrent thread to sneak in (see concurrency).

  • delete returns whether a database row was deleted or not.

All primary keys are supported, including composite primary keys that span several columns, and the implicit rowid primary key.

Customizing the Persistence Methods

Your custom type may want to perform extra work when the persistence methods are invoked.

For example, it may want to have its UUID automatically set before inserting. Or it may want to validate its values before saving.

When you subclass Record, you simply have to override the customized method, and call super:

class Player : Record {
    var uuid: UUID?

    override func insert(_ db: Database) throws {
        if uuid == nil {
            uuid = UUID()
        }
        try super.insert(db)
    }
}

If you use the raw Persistable protocol, use one of the special methods performInsert, performUpdate, performSave, performDelete, or performExists:

struct Link : Persistable {
    var url: URL

    func insert(_ db: Database) throws {
        try validate()
        try performInsert(db)
    }

    func update(_ db: Database, columns: Set<String>) throws {
        try validate()
        try performUpdate(db, columns: columns)
    }

    func validate() throws {
        if url.host == nil {
            throw ValidationError("url must be absolute.")
        }
    }
}

:point_up: Note: the special methods performInsert, performUpdate, etc. are reserved for your custom implementations. Do not use them elsewhere. Do not provide another implementation for those methods.

:point_up: Note: it is recommended that you do not implement your own version of the save method. Its default implementation forwards the job to update or insert: these are the methods that may need customization, not save.

Codable Records

Swift Archival & Serialization was introduced with Swift 4.

GRDB provides default implementations for RowConvertible.init(row:) and Persistable.encode(to:) for record types that also adopt an archival protocol (Codable, Encodable or Decodable). When all their properties are themselves codable, Swift generates the archiving methods, and you don’t need to write them down:

// Declare a plain Codable struct or class...
struct Player: Codable {
    let name: String
    let score: Int
}

// Adopt Record protocols...
extension Player: RowConvertible, Persistable {
    static let databaseTableName = "players"
}

// ...and you can save and fetch players:
try dbQueue.inDatabase { db in
    try Player(name: "Arthur", score: 100).insert(db)
    let players = try Player.fetchAll(db)
}

GRDB support for Codable works well with flat records, whose stored properties are all simple values (Bool, Int, String, Date, Swift enums, etc.) For example, the following record is not flat:

// Can't take profit from Codable code generation:
struct Place: RowConvertible, Persistable, Codable {
    static let databaseTableName = "places"

    var title: String
    var coordinate: CLLocationCoordinate2D // <- Not a simple value!
}

Make it flat, as below, and you’ll be granted with all Codable and GRDB advantages:

struct Place: Codable {
    // Stored properties are plain values:
    var title: String
    var latitude: CLLocationDegrees
    var longitude: CLLocationDegrees

    // Complex property is computed:
    var coordinate: CLLocationCoordinate2D {
        get {
            return CLLocationCoordinate2D(
                latitude: latitude,
                longitude: longitude)
        }
        set {
            latitude = newValue.latitude
            longitude = newValue.longitude
        }
    }
}

// Free database support!
extension Place: RowConvertible, Persistable {
    static let databaseTableName = "places"
}

GRDB ships with support for nested codable records, but this is a more complex topic. See Joined Queries Support for more information.

As documented with the Persistable protocol, have your struct records use MutablePersistable instead of Persistable when they store their automatically incremented row id:

struct Place: Codable {
    var id: Int64?      // <- the row id
    var title: String
    var latitude: CLLocationDegrees
    var longitude: CLLocationDegrees
    var coordinate: CLLocationCoordinate2D { ... }
}

extension Place: RowConvertible, MutablePersistable {
    static let databaseTableName = "places"

    mutating func didInsert(with rowID: Int64, for column: String?) {
        // Update id after insertion
        id = rowID
    }
}

var place = Place(id: nil, ...)
try place.insert(db)
place.id // A unique id

:point_up: Note: Some values have a different way to encode and decode themselves in a standard archive vs. the database. For example, Date saves itself as a numerical timestamp (archive) or a string (database). When such an ambiguity happens, GRDB always favors customized database encoding and decoding.

Record Class

Record is a class that is designed to be subclassed. It inherits its features from the RowConvertible, TableMapping, and Persistable protocols. On top of that, Record instances can track their changes.

Record subclasses define their custom database relationship by overriding database methods:

class Place : Record {
    var id: Int64?
    var title: String
    var coordinate: CLLocationCoordinate2D

    /// The table name
    override class var databaseTableName: String {
        return "places"
    }

    /// Initialize from a database row
    required init(row: Row) {
        id = row["id"]
        title = row["title"]
        coordinate = CLLocationCoordinate2D(
            latitude: row["latitude"],
            longitude: row["longitude"])
        super.init(row: row)
    }

    /// The values persisted in the database
    override func encode(to container: inout PersistenceContainer) {
        container["id"] = id
        container["title"] = title
        container["latitude"] = coordinate.latitude
        container["longitude"] = coordinate.longitude
    }

    /// When relevant, update record ID after a successful insertion
    override func didInsert(with rowID: Int64, for column: String?) {
        id = rowID
    }
}

Changes Tracking

Changes tracking is the ability, for a record, to compare against another record, or against previous versions of itself.

The update() method always executes an UPDATE statement. When the record has not been edited, this costly database access is generally useless.

You can use instead the updateChanges method, available on the Persistable protocol, which performs an update of the changed columns only (and does nothing if record has no change):

let oldPlayer = try Player.fetchOne(db, ...)
var newPlayer = oldPlayer
newPlayer.score = 100
if try newPlayer.updateChanges(db, from: oldPlayer) {
    print("player was modified")
} else {
    print("player was not modified")
}

:point_up: Note: The comparison is performed of the database representation of records. As long as your record type adopts a Persistable protocol, you don’t need to care about Equatable.

The Record class is able to compare against itself, and knows if it has changes that have not been saved since it was last fetched or persisted:

// Record class only
let player = try Player.fetchOne(db, ...)
player.score = 100
if try player.updateChanges(db) {
    print("player was modified")
} else {
    print("player was not modified")
}

You can also use the databaseEqual method, which returns whether two records have the same database representation:

let oldPlayer: Player = ...
var newPlayer: Player = ...
if newPlayer.databaseEqual(oldPlayer) == false {
    try newPlayer.save(db)
}

Again, Record instances can compare against themselves, with the hasDatabaseChanges property:

// Record class only
player.score = 100
if player.hasDatabaseChanges {
    try player.save(db)
}

Record.hasDatabaseChanges is false after a Record instance has been fetched or saved into the database. Subsequent modifications may set it, or not: hasDatabaseChanges is based on value comparison. Setting a property to the same value does not set the changed flag:

let player = Player(name: "Barbara", score: 750)
player.hasDatabaseChanges // true

try player.insert(db)
player.hasDatabaseChanges // false

player.name = "Barbara"
player.hasDatabaseChanges // false

player.score = 1000
player.hasDatabaseChanges // true
player.databaseChanges    // ["score": 750]

For an efficient algorithm which synchronizes the content of a database table with a JSON payload, check JSONSynchronization.playground.

Conflict Resolution

Insertions and updates can create conflicts: for example, a query may attempt to insert a duplicate row that violates a unique index.

Those conflicts normally end with an error. Yet SQLite let you alter the default behavior, and handle conflicts with specific policies. For example, the INSERT OR REPLACE statement handles conflicts with the replace policy which replaces the conflicting row instead of throwing an error.

The five different policies are: abort (the default), replace, rollback, fail, and ignore.

SQLite let you specify conflict policies at two different places:

  • At the table level

    // CREATE TABLE players (
//     id INTEGER PRIMARY KEY,
//     email TEXT UNIQUE ON CONFLICT REPLACE
// )
try db.create(table: "players") { t in
    t.column("id", .integer).primaryKey()
    t.column("email", .text).unique(onConflict: .replace) // <--
}

// Despite the unique index on email, both inserts succeed.
// The second insert replaces the first row:
try db.execute("INSERT INTO players (email) VALUES (?)", arguments: ["arthur@example.com"])
try db.execute("INSERT INTO players (email) VALUES (?)", arguments: ["arthur@example.com"])

  • At the query level:

    // CREATE TABLE players (
//     id INTEGER PRIMARY KEY,
//     email TEXT UNIQUE
// )
try db.create(table: "players") { t in
    t.column("id", .integer).primaryKey()
    t.column("email", .text)
}

// Again, despite the unique index on email, both inserts succeed.
try db.execute("INSERT OR REPLACE INTO players (email) VALUES (?)", arguments: ["arthur@example.com"])
try db.execute("INSERT OR REPLACE INTO players (email) VALUES (?)", arguments: ["arthur@example.com"])

When you want to handle conflicts at the query level, specify a custom persistenceConflictPolicy in your type that adopts the MutablePersistable or Persistable protocol. It will alter the INSERT and UPDATE queries run by the insert, update and save persistence methods:

protocol MutablePersistable {
    /// The policy that handles SQLite conflicts when records are inserted
    /// or updated.
    ///
    /// This property is optional: its default value uses the ABORT policy
    /// for both insertions and updates, and has GRDB generate regular
    /// INSERT and UPDATE queries.
    static var persistenceConflictPolicy: PersistenceConflictPolicy { get }
}

struct Player : MutablePersistable {
    static let persistenceConflictPolicy = PersistenceConflictPolicy(
        insert: .replace,
        update: .replace)
}

// INSERT OR REPLACE INTO players (...) VALUES (...)
try player.insert(db)

:point_up: Note: the ignore policy does not play well at all with the didInsert method which notifies the rowID of inserted records. Choose your poison:

  • if you specify the ignore policy at the table level, don’t implement the didInsert method: it will be called with some random id in case of failed insert.
  • if you specify the ignore policy at the query level, the didInsert method is never called.

:warning: Warning: ON CONFLICT REPLACE may delete rows so that inserts and updates can succeed. Those deletions are not reported to transaction observers (this might change in a future release of SQLite).

The Implicit RowID Primary Key

All SQLite tables have a primary key. Even when the primary key is not explicit:

// No explicit primary key
try db.create(table: "events") { t in
    t.column("message", .text)
    t.column("date", .datetime)
}

// No way to define an explicit primary key
try db.create(virtualTable: "books", using: FTS4()) { t in
    t.column("title")
    t.column("author")
    t.column("body")
}

The implicit primary key is stored in the hidden column rowid. Hidden means that SELECT * does not select it, and yet it can be selected and queried: SELECT *, rowid ... WHERE rowid = 1.

Some GRDB methods will automatically use this hidden column when a table has no explicit primary key:

// SELECT * FROM events WHERE rowid = 1
let event = try Event.fetchOne(db, key: 1)

// DELETE FROM books WHERE rowid = 1
try Book.deleteOne(db, key: 1)

Exposing the RowID Column

By default, a record type that wraps a table without any explicit primary key doesn’t know about the hidden rowid column.

Without primary key, records don’t have any identity, and the persistence method can behave in undesired fashion: update() throws errors, save() always performs insertions and may break constraints, exists() is always false.

When SQLite won’t let you provide an explicit primary key (as in full-text tables, for example), you may want to make your record type fully aware of the hidden rowid column:

  1. Have the databaseSelection static property (from the TableMapping protocol) return the hidden rowid column:

    struct Event : TableMapping {
    static let databaseSelection: [SQLSelectable] = [AllColumns(), Column.rowID]
}

// When you subclass Record, you need an override:
class Book : Record {
    override class var databaseSelection: [SQLSelectable] {
        return [AllColums(), Column.rowID]
    }
}

    GRDB will then select the rowid column by default:

    // SELECT *, rowid FROM events
let events = try Event.fetchAll(db)

  2. Have init(row:) from the RowConvertible protocol consume the rowid column:

    struct Event : RowConvertible {
    var id: Int64?

    init(row: Row) {
        id = row["rowid"]
    }
}

    If you prefer using the Column type from the query interface, use the Column.rowID constant:

    init(row: Row) {
    id = row[.rowID]
}

    Your fetched records will then know their ids:

    let event = try Event.fetchOne(db)!
event.id // some value

  3. Encode the rowid in encode(to:), and keep it in the didInsert(with:for:) method (both from the Persistable and MutablePersistable protocols):

    struct Event : MutablePersistable {
    var id: Int64?

    func encode(to container: inout PersistenceContainer) {
        container[.rowID] = id
        container["message"] = message
        container["date"] = date
    }

    mutating func didInsert(with rowID: Int64, for column: String?) {
        id = rowID
    }
}

    You will then be able to track your record ids, update them, or check for their existence:

    let event = Event(message: "foo", date: Date())

// Insertion sets the record id:
try event.insert(db)
event.id // some value

// Record can be updated:
event.message = "bar"
try event.update(db)

// Record knows if it exists:
event.exists(db) // true

List of Record Methods

This is the list of record methods, along with their required protocols. The Record adopts all these protocols, and adds a few extra methods.

Method Protocols Notes
Core Methods
init(row:) RowConvertible
Type.databaseTableName TableMapping
Type.databaseSelection TableMapping *
Type.persistenceConflictPolicy Persistable *
record.encode(to:) Persistable
record.didInsert(with:for:) Persistable
Insert and Update Records
record.insert(db) Persistable
record.save(db) Persistable
record.update(db) Persistable
record.update(db, columns:...) Persistable
record.updateChanges(db, from:...) Persistable
record.updateChanges(db) Record
Delete Records
record.delete(db) Persistable
Type.deleteOne(db, key:...) Persistable ¹
Type.deleteAll(db) Persistable
Type.deleteAll(db, keys:...) Persistable ¹
Type.filter(...).deleteAll(db) Persistable ²
Check Record Existence
record.exists(db) Persistable
Convert Record to Dictionary
record.databaseDictionary Persistable
Count Records
Type.fetchCount(db) TableMapping
Type.filter(...).fetchCount(db) TableMapping ²
Fetch Record Cursors
Type.fetchCursor(db) RowConvertible & TableMapping
Type.fetchCursor(db, keys:...) RowConvertible & TableMapping ¹
Type.fetchCursor(db, sql) RowConvertible ³
Type.fetchCursor(statement) RowConvertible ⁴
Type.filter(...).fetchCursor(db) RowConvertible & TableMapping ²
Fetch Record Arrays
Type.fetchAll(db) RowConvertible & TableMapping
Type.fetchAll(db, keys:...) RowConvertible & TableMapping ¹
Type.fetchAll(db, sql) RowConvertible ³
Type.fetchAll(statement) RowConvertible ⁴
Type.filter(...).fetchAll(db) RowConvertible & TableMapping ²
Fetch Individual Records
Type.fetchOne(db) RowConvertible & TableMapping
Type.fetchOne(db, key:...) RowConvertible & TableMapping ¹
Type.fetchOne(db, sql) RowConvertible ³
Type.fetchOne(statement) RowConvertible ⁴
Type.filter(...).fetchOne(db) RowConvertible & TableMapping ²
Changes Tracking
record.databaseEqual(...) Persistable
record.databaseChanges(from:...) Persistable
record.updateChanges(db, from:...) Persistable
record.hasDatabaseChanges Record
record.databaseChanges Record
record.updateChanges(db) Record

¹ All unique keys are supported: primary keys (single-column, composite, implicit RowID) and unique indexes:

try Player.fetchOne(db, key: 1)                               // Player?
try Player.fetchOne(db, key: ["email": "arthur@example.com"]) // Player?
try Country.fetchAll(db, keys: ["FR", "US"])                  // [Country]

² See Fetch Requests:

let request = Player.filter(emailColumn != nil).order(nameColumn)
let players = try request.fetchAll(db)  // [Player]
let count = try request.fetchCount(db)  // Int

³ See SQL queries:

let player = try Player.fetchOne("SELECT * FROM players WHERE id = ?", arguments: [1]) // Player?

⁴ See Prepared Statements:

let statement = try db.makeSelectStatement("SELECT * FROM players WHERE id = ?")
let player = try Player.fetchOne(statement, arguments: [1])  // Player?

The Query Interface

The query interface lets you write pure Swift instead of SQL:

try dbQueue.inDatabase { db in
    // Update database schema
    try db.create(table: "wines") { t in ... }

    // Fetch records
    let wines = try Wine.filter(origin == "Burgundy").order(price).fetchAll(db)

    // Count
    let count = try Wine.filter(color == Color.red).fetchCount(db)

    // Delete
    try Wine.filter(corked == true).deleteAll(db)
}

You need to open a database connection before you can query the database.

Please bear in mind that the query interface can not generate all possible SQL queries. You may also prefer writing SQL, and this is just OK. From little snippets to full queries, your SQL skills are welcome:

try dbQueue.inDatabase { db in
    // Update database schema (with SQL)
    try db.execute("CREATE TABLE wines (...)")

    // Fetch records (with SQL)
    let wines = try Wine.fetchAll(db,
        "SELECT * FROM wines WHERE origin = ? ORDER BY price",
        arguments: ["Burgundy"])

    // Count (with an SQL snippet)
    let count = try Wine
        .filter(sql: "color = ?", arguments: [Color.red])
        .fetchCount(db)

    // Delete (with SQL)
    try db.execute("DELETE FROM wines WHERE corked")
}

So don’t miss the SQL API.

Database Schema

Once granted with a database connection, you can setup your database schema without writing SQL:

Create Tables

// CREATE TABLE places (
//   id INTEGER PRIMARY KEY,
//   title TEXT,
//   favorite BOOLEAN NOT NULL DEFAULT 0,
//   latitude DOUBLE NOT NULL,
//   longitude DOUBLE NOT NULL
// )
try db.create(table: "places") { t in
    t.column("id", .integer).primaryKey()
    t.column("title", .text)
    t.column("favorite", .boolean).notNull().defaults(to: false)
    t.column("longitude", .double).notNull()
    t.column("latitude", .double).notNull()
}

The create(table:) method covers nearly all SQLite table creation features. For virtual tables, see Full-Text Search, or use raw SQL.

SQLite has many reference documents about table creation:

Configure table creation:

// CREATE TABLE example ( ... )
try db.create(table: "example") { t in ... }

// CREATE TEMPORARY TABLE example IF NOT EXISTS (
try db.create(table: "example", temporary: true, ifNotExists: true) { t in

Add regular columns with their name and eventual type (text, integer, double, numeric, boolean, blob, date and datetime) - see SQLite data types:

// CREATE TABLE example (
//   a,
//   name TEXT,
//   creationDate DATETIME,
try db.create(table: "example") { t in ... }
    t.column("a")
    t.column("name", .text)
    t.column("creationDate", .datetime)

Define not null columns, and set default values:

    // email TEXT NOT NULL,
    t.column("email", .text).notNull()

    // name TEXT NOT NULL DEFAULT 'Anonymous',
    t.column("name", .text).notNull().defaults(to: "Anonymous")

Use an individual column as primary, unique, or foreign key. When defining a foreign key, the referenced column is the primary key of the referenced table (unless you specify otherwise):

    // id INTEGER PRIMARY KEY,
    t.column("id", .integer).primaryKey()

    // email TEXT UNIQUE,
    t.column("email", .text).unique()

    // countryCode TEXT REFERENCES countries(code) ON DELETE CASCADE,
    t.column("countryCode", .text).references("countries", onDelete: .cascade)

Create an index on the column:

    t.column("score", .integer).indexed()

For extra index options, see Create Indexes below.

Perform integrity checks on individual columns, and SQLite will only let conforming rows in. In the example below, the $0 closure variable is a column which lets you build any SQL expression.

    // name TEXT CHECK (LENGTH(name) > 0)
    // score INTEGER CHECK (score > 0)
    t.column("name", .text).check { length($0) > 0 }
    t.column("score", .integer).check(sql: "score > 0")

Other table constraints can involve several columns:

    // PRIMARY KEY (a, b),
    t.primaryKey(["a", "b"])

    // UNIQUE (a, b) ON CONFLICT REPLACE,
    t.uniqueKey(["a", "b"], onConfict: .replace)

    // FOREIGN KEY (a, b) REFERENCES parents(c, d),
    t.foreignKey(["a", "b"], references: "parent")

    // CHECK (a + b < 10),
    t.check(Column("a") + Column("b") < 10)

    // CHECK (a + b < 10)
    t.check(sql: "a + b < 10")
}

Modify Tables

SQLite lets you rename tables, and add columns to existing tables:

// ALTER TABLE referers RENAME TO referrers
try db.rename(table: "referers", to: "referrers")

// ALTER TABLE players ADD COLUMN url TEXT
try db.alter(table: "players") { t in
    t.add(column: "url", .text)
}

:point_up: Note: SQLite restricts the possible table alterations, and may require you to recreate dependent triggers or views. See the documentation of the ALTER TABLE for details. See Advanced Database Schema Changes for a way to lift restrictions.

Drop Tables

Drop tables with the drop(table:) method:

try db.drop(table: "obsolete")

Create Indexes

Create indexes with the create(index:) method:

// CREATE UNIQUE INDEX byEmail ON users(email)
try db.create(index: "byEmail", on: "users", columns: ["email"], unique: true)

Relevant SQLite documentation:

Requests

The query interface requests let you fetch values from the database:

let request = Player.filter(emailColumn != nil).order(nameColumn)
let players = try request.fetchAll(db)  // [Player]
let count = try request.fetchCount(db)  // Int

All requests start from a type that adopts the TableMapping protocol, such as a Record subclass (see Records):

class Player : Record { ... }

Declare the table columns that you want to use for filtering, or sorting:

let idColumn = Column("id")
let nameColumn = Column("name")

You can now build requests with the following methods: all, none, select, distinct, filter, matching, group, having, order, reversed, limit. All those methods return another request, which you can further refine by applying another method: Player.select(...).filter(...).order(...).

  • all(), none(): the requests for all rows, or no row.

    // SELECT * FROM players
Player.all()

    The hidden rowid column can be selected as well when you need it.

  • select(expression, ...) defines the selected columns.

    // SELECT id, name FROM players
Player.select(idColumn, nameColumn)

// SELECT MAX(score) AS maxScore FROM players
Player.select(max(scoreColumn).aliased("maxScore"))

  • distinct() performs uniquing.

    // SELECT DISTINCT name FROM players
Player.select(nameColumn).distinct()

  • filter(expression) applies conditions.

    // SELECT * FROM players WHERE id IN (1, 2, 3)
Player.filter([1,2,3].contains(idColumn))

// SELECT * FROM players WHERE (name IS NOT NULL) AND (height > 1.75)
Player.filter(nameColumn != nil && heightColumn > 1.75)

  • filter(key:) and filter(keys:) apply conditions on primary keys and unique keys:

    // SELECT * FROM players WHERE id = 1
Player.filter(key: 1)

// SELECT * FROM countries WHERE isoCode IN ('FR', 'US')
Country.filter(keys: ["FR", "US"])

// SELECT * FROM citizenships WHERE playerID = 1 AND countryISOCode = 'FR'
Citizenship.filter(key: ["playerID": 1, "countryISOCode": "FR"])

// SELECT * FROM players WHERE email = 'arthur@example.com'
Player.filter(key: ["email": "arthur@example.com"])

  • matching(pattern) performs full-text search.

    // SELECT * FROM documents WHERE documents MATCH 'sqlite database'
let pattern = FTS3Pattern(matchingAllTokensIn: "SQLite database")
Document.matching(pattern)

    When the pattern is nil, no row will match.

  • group(expression, ...) groups rows.

    // SELECT name, MAX(score) FROM players GROUP BY name
Player
    .select(nameColumn, max(scoreColumn))
    .group(nameColumn)

  • having(expression) applies conditions on grouped rows.

    // SELECT team, MAX(score) FROM players GROUP BY team HAVING MIN(score) >= 1000
Player
    .select(teamColumn, max(scoreColumn))
    .group(teamColumn)
    .having(min(scoreColumn) >= 1000)

  • order(ordering, ...) sorts.

    // SELECT * FROM players ORDER BY name
Player.order(nameColumn)

// SELECT * FROM players ORDER BY score DESC, name
Player.order(scoreColumn.desc, nameColumn)

    Each order call clears any previous ordering:

    // SELECT * FROM players ORDER BY name
Player.order(scoreColumn).order(nameColumn)

  • reversed() reverses the eventual orderings.

    // SELECT * FROM players ORDER BY score ASC, name DESC
Player.order(scoreColumn.desc, nameColumn).reversed()

    If no ordering was specified, the result is ordered by rowID in reverse order.

    // SELECT * FROM players ORDER BY _rowid_ DESC
Player.all().reversed()

  • limit(limit, offset: offset) limits and pages results.

    // SELECT * FROM players LIMIT 5
Player.limit(5)

// SELECT * FROM players LIMIT 5 OFFSET 10
Player.limit(5, offset: 10)

You can refine requests by chaining those methods:

// SELECT * FROM players WHERE (email IS NOT NULL) ORDER BY name
Player.order(nameColumn).filter(emailColumn != nil)

The select, order, group, and limit methods ignore and replace previously applied selection, orderings, grouping, and limits. On the opposite, filter, matching, and having methods extend the query:

Player                          // SELECT * FROM players
    .filter(nameColumn != nil)  // WHERE (name IS NOT NULL)
    .filter(emailColumn != nil) //        AND (email IS NOT NULL)
    .order(nameColumn)          // - ignored -
    .order(scoreColumn)         // ORDER BY score
    .limit(20, offset: 40)      // - ignored -
    .limit(10)                  // LIMIT 10

Raw SQL snippets are also accepted, with eventual arguments:

// SELECT DATE(creationDate), COUNT(*) FROM players WHERE name = 'Arthur' GROUP BY date(creationDate)
Player
    .select(sql: "DATE(creationDate), COUNT(*)")
    .filter(sql: "name = ?", arguments: ["Arthur"])
    .group(sql: "DATE(creationDate)")

Columns Selected by a Request

By default, query interface requests select all columns:

// SELECT * FROM players
let request = Player.all()

The selection can be changed for each individual requests, or for all requests built from a given type.

To specify the selection of a specific request, use the select method:

// SELECT id, name FROM players
let request = Player.select(Column("id"), Column("name"))

// SELECT *, rowid FROM players
let request = Player.select(AllColumns(), Column.rowID)

To specify the default selection for all requests built from a type, define the databaseSelection property:

struct RestrictedPlayer : TableMapping {
    static let databaseTableName = "players"
    static let databaseSelection: [SQLSelectable] = [Column("id"), Column("name")]
}

struct ExtendedPlayer : TableMapping {
    static let databaseTableName = "players"
    static let databaseSelection: [SQLSelectable] = [AllColumns(), Column.rowID]
}

// SELECT id, name FROM players
let request = RestrictedPlayer.all()

// SELECT *, rowid FROM players
let request = ExtendedPlayer.all()

:point_up: Note: make sure the databaseSelection property is explicitely declared as [SQLSelectable]. If it is not, the Swift compiler may infer a type which may silently miss the protocol requirement, resulting in sticky SELECT * requests.

Expressions

Feed requests with SQL expressions built from your Swift code:

SQL Operators

  • =, <>, <, <=, >, >=, IS, IS NOT

    Comparison operators are based on the Swift operators ==, !=, ===, !==, <, <=, >, >=:

    // SELECT * FROM players WHERE (name = 'Arthur')
Player.filter(nameColumn == "Arthur")

// SELECT * FROM players WHERE (name IS NULL)
Player.filter(nameColumn == nil)

// SELECT * FROM players WHERE (score IS 1000)
Player.filter(scoreColumn === 1000)

// SELECT * FROM rectangles WHERE width < height
Rectangle.filter(widthColumn < heightColumn)

    :point_up: Note: SQLite string comparison, by default, is case-sensitive and not Unicode-aware. See string comparison if you need more control.

  • *, /, +, -

    SQLite arithmetic operators are derived from their Swift equivalent:

    // SELECT ((temperature * 1.8) + 32) AS farenheit FROM players
Planet.select((temperatureColumn * 1.8 + 32).aliased("farenheit"))

    :point_up: Note: an expression like nameColumn + "rrr" will be interpreted by SQLite as a numerical addition (with funny results), not as a string concatenation.

  • AND, OR, NOT

    The SQL logical operators are derived from the Swift &&, || and !:

    // SELECT * FROM players WHERE ((NOT verified) OR (score < 1000))
Player.filter(!verifiedColumn || scoreColumn < 1000)

  • BETWEEN, IN, NOT IN

    To check inclusion in a Swift sequence (array, set, range…), call the contains method:

    // SELECT * FROM players WHERE id IN (1, 2, 3)
Player.filter([1, 2, 3].contains(idColumn))

// SELECT * FROM players WHERE id NOT IN (1, 2, 3)
Player.filter(![1, 2, 3].contains(idColumn))

// SELECT * FROM players WHERE score BETWEEN 0 AND 1000
Player.filter((0...1000).contains(scoreColumn))

// SELECT * FROM players WHERE (score >= 0) AND (score < 1000)
Player.filter((0..<1000).contains(scoreColumn))

// SELECT * FROM players WHERE initial BETWEEN 'A' AND 'N'
Player.filter(("A"..."N").contains(initialColumn))

// SELECT * FROM players WHERE (initial >= 'A') AND (initial < 'N')
Player.filter(("A"..<"N").contains(initialColumn))

    :point_up: Note: SQLite string comparison, by default, is case-sensitive and not Unicode-aware. See string comparison if you need more control.

  • LIKE

    The SQLite LIKE operator is available as the like method:

    // SELECT * FROM players WHERE (email LIKE '%@example.com')
Player.filter(emailColumn.like("%@example.com"))

    :point_up: Note: the SQLite LIKE operator is case-unsensitive but not Unicode-aware. For example, the expression 'a' LIKE 'A' is true but 'æ' LIKE 'Æ' is false.

  • MATCH

    The full-text MATCH operator is available through FTS3Pattern (for FTS3 and FTS4 tables) and FTS5Pattern (for FTS5):

    FTS3 and FTS4:

    let pattern = FTS3Pattern(matchingAllTokensIn: "SQLite database")

// SELECT * FROM documents WHERE documents MATCH 'sqlite database'
Document.matching(pattern)

// SELECT * FROM documents WHERE content MATCH 'sqlite database'
Document.filter(contentColumn.match(pattern))

    FTS5:

    let pattern = FTS5Pattern(matchingAllTokensIn: "SQLite database")

// SELECT * FROM documents WHERE documents MATCH 'sqlite database'
Document.matching(pattern)

SQL Functions

  • ABS, AVG, COUNT, LENGTH, MAX, MIN, SUM:

    Those are based on the abs, average, count, length, max, min and sum Swift functions:

    // SELECT MIN(score), MAX(score) FROM players
Player.select(min(scoreColumn), max(scoreColumn))

// SELECT COUNT(name) FROM players
Player.select(count(nameColumn))

// SELECT COUNT(DISTINCT name) FROM players
Player.select(count(distinct: nameColumn))

  • IFNULL

    Use the Swift ?? operator:

    // SELECT IFNULL(name, 'Anonymous') FROM players
Player.select(nameColumn ?? "Anonymous")

// SELECT IFNULL(name, email) FROM players
Player.select(nameColumn ?? emailColumn)

  • LOWER, UPPER

    The query interface does not give access to those SQLite functions. Nothing against them, but they are not unicode aware.

    Instead, GRDB extends SQLite with SQL functions that call the Swift built-in string functions capitalized, lowercased, uppercased, localizedCapitalized, localizedLowercased and localizedUppercased:

    Player.select(nameColumn.uppercased())

    :point_up: Note: When comparing strings, you’d rather use a collation:

    let name: String = ...

// Not recommended
nameColumn.uppercased() == name.uppercased()

// Better
nameColumn.collating(.caseInsensitiveCompare) == name

  • Custom SQL functions and aggregates

    You can apply your own custom SQL functions and aggregates:

    let f = DatabaseFunction("f", ...)

// SELECT f(name) FROM players
Player.select(f.apply(nameColumn))

Fetching from Requests

Once you have a request, you can fetch the records at the origin of the request:

// Some request based on `Player`
let request = Player.filter(...)... // QueryInterfaceRequest<Player>

// Fetch players:
try request.fetchCursor(db) // A Cursor of Player
try request.fetchAll(db)    // [Player]
try request.fetchOne(db)    // Player?

See fetching methods for information about the fetchCursor, fetchAll and fetchOne methods.

For example:

let allPlayers = try Player.fetchAll(db)                            // [Player]
let arthur = try Player.filter(nameColumn == "Arthur").fetchOne(db) // Player?

When the selected columns don’t fit the source type, change your target: any other type that adopts the RowConvertible protocol, plain database rows, and even values:

let maxScore = try Player.select(max(scoreColumn))
    .asRequest(of: Int.self)
    .fetchOne(db) // Int?

let row = try Player.select(min(scoreColumn), max(scoreColumn))
    .asRequest(of: Row.self)
    .fetchOne(db)!
let minScore = row[0] as Int?
let maxScore = row[1] as Int?

More information about asRequest(of:) can be found in the Custom Requests chapter.

Fetching By Key

Fetching records according to their primary key is a very common task. It has a shortcut which accepts any single-column primary key:

// SELECT * FROM players WHERE id = 1
try Player.fetchOne(db, key: 1)              // Player?

// SELECT * FROM players WHERE id IN (1, 2, 3)
try Player.fetchAll(db, keys: [1, 2, 3])     // [Player]

// SELECT * FROM players WHERE isoCode = 'FR'
try Country.fetchOne(db, key: "FR")          // Country?

// SELECT * FROM countries WHERE isoCode IN ('FR', 'US')
try Country.fetchAll(db, keys: ["FR", "US"]) // [Country]

When the table has no explicit primary key, GRDB uses the hidden rowid column:

// SELECT * FROM documents WHERE rowid = 1
try Document.fetchOne(db, key: 1)            // Document?

For multiple-column primary keys and unique keys defined by unique indexes, provide a dictionary:

// SELECT * FROM citizenships WHERE playerID = 1 AND countryISOCode = 'FR'
try Citizenship.fetchOne(db, key: ["playerID": 1, "countryISOCode": "FR"]) // Citizenship?

// SELECT * FROM players WHERE email = 'arthur@example.com'
try Player.fetchOne(db, key: ["email": "arthur@example.com"])              // Player?

When you want to build a request and plan to fetch from it later, use the filter(key:) and filter(keys:) methods:

// SELECT * FROM players WHERE id = 1
let request = Player.filter(key: 1)
let player = try request.fetchOne(db)    // Player?

// SELECT * FROM players WHERE id IN (1, 2, 3)
let request = Player.filter(keys: [1, 2, 3])
let players = try request.fetchAll(db)   // [Player]

// SELECT * FROM players WHERE isoCode = 'FR'
let request = Country.filter(key: "FR")
let country = try request.fetchOne(db)   // Country?

// SELECT * FROM countries WHERE isoCode IN ('FR', 'US')
let request = Country.filter(keys: ["FR", "US"])
let countries = try request.fetchAll(db) // [Country]

// SELECT * FROM citizenships WHERE playerID = 1 AND countryISOCode = 'FR'
let request = Citizenship.filter(key: ["playerID": 1, "countryISOCode": "FR"])
let citizenship = request.fetchOne(db)   // Citizenship?

// SELECT * FROM players WHERE email = 'arthur@example.com'
let request = Player.filter(key: ["email": "arthur@example.com"])
let player = try request.fetchOne(db)    // Player?

Those requests help observing the database with FetchedRecordsController or RxGRDB:

Player.filter(key: 1).rx
    .fetchOne(in: dbQueue)
    .subscribe(onNext: { player: Player? in
        print("Player 1 has changed")
    })

Fetching Aggregated Values

Requests can count. The fetchCount() method returns the number of rows that would be returned by a fetch request:

// SELECT COUNT(*) FROM players
let count = try Player.fetchCount(db) // Int

// SELECT COUNT(*) FROM players WHERE email IS NOT NULL
let count = try Player.filter(emailColumn != nil).fetchCount(db)

// SELECT COUNT(DISTINCT name) FROM players
let count = try Player.select(nameColumn).distinct().fetchCount(db)

// SELECT COUNT(*) FROM (SELECT DISTINCT name, score FROM players)
let count = try Player.select(nameColumn, scoreColumn).distinct().fetchCount(db)

Other aggregated values can also be selected and fetched (see SQL Functions):

let maxScore = try Player.select(max(scoreColumn))
    .asRequest(of: Int.self)
    .fetchOne(db) // Int?

let row = try Player.select(min(scoreColumn), max(scoreColumn))
    .asRequest(of: Row.self)
    .fetchOne(db)!
let minScore = row[0] as Int?
let maxScore = row[1] as Int?

More information about asRequest(of:) can be found in the Custom Requests chapter.

Delete Requests

Requests can delete records, with the deleteAll() method:

// DELETE FROM players WHERE email IS NULL
let request = Player.filter(emailColumn == nil)
try request.deleteAll(db)

:point_up: Note Deletion methods are only available for records that adopts the Persistable protocol.

Deleting records according to their primary key is also quite common. It has a shortcut which accepts any single-column primary key:

// DELETE FROM players WHERE id = 1
try Player.deleteOne(db, key: 1)

// DELETE FROM players WHERE id IN (1, 2, 3)
try Player.deleteAll(db, keys: [1, 2, 3])

// DELETE FROM players WHERE isoCode = 'FR'
try Country.deleteOne(db, key: "FR")

// DELETE FROM countries WHERE isoCode IN ('FR', 'US')
try Country.deleteAll(db, keys: ["FR", "US"])

When the table has no explicit primary key, GRDB uses the hidden rowid column:

// DELETE FROM documents WHERE rowid = 1
try Document.deleteOne(db, key: 1)

For multiple-column primary keys and unique keys defined by unique indexes, provide a dictionary:

// DELETE FROM citizenships WHERE playerID = 1 AND countryISOCode = 'FR'
try Citizenship.deleteOne(db, key: ["playerID": 1, "countryISOCode": "FR"])

// DELETE FROM players WHERE email = 'arthur@example.com'
Player.deleteOne(db, key: ["email": "arthur@example.com"])

Custom Requests

Until now, we have seen requests created from any type that adopts the TableMapping protocol:

let request = Player.all()  // QueryInterfaceRequest<Player>

Those requests of type QueryInterfaceRequest can fetch, count, and delete records:

try request.fetchCursor(db) // A Cursor of Player
try request.fetchAll(db)    // [Player]
try request.fetchOne(db)    // Player?
try request.fetchCount(db)  // Int
try request.deleteAll(db)

When the query interface can not generate the SQL you need, you can still fallback to raw SQL:

// Custom SQL is always welcome
try Player.fetchAll(db, "SELECT ...")   // [Player]

But you may prefer to bring some elegance back in, and build custom requests on top of the Request and TypedRequest protocols:

// No custom SQL in sight
try Player.customRequest().fetchAll(db) // [Player]

Unlike QueryInterfaceRequest, these protocols can’t delete. But they can fetch and count:

/// The protocol for all types that define a way to fetch database rows.
protocol Request {
    /// A tuple that contains a prepared statement that is ready to be
    /// executed, and an eventual row adapter.
    func prepare(_ db: Database) throws -> (SelectStatement, RowAdapter?)

    /// The number of rows fetched by the request.
    func fetchCount(_ db: Database) throws -> Int
}

/// The protocol for requests that know how to decode database rows.
protocol TypedRequest : Request {
    /// The type that can convert raw database rows to fetched values
    associatedtype RowDecoder
}

The prepare method returns a tuple made of a prepared statement and an optional row adapter. The prepared statement tells which SQL query should be executed. The row adapter can help presenting the fetched rows in the way expected by the row consumers (we’ll see an example below).

The fetchCount method has a default implementation that builds a correct but naive SQL query from the statement returned by prepare: SELECT COUNT(*) FROM (...). Adopting types can refine the counting SQL by customizing their fetchCount implementation.

Fetching From Custom Requests

A Request doesn’t know what to fetch, but it can feed the fetching methods of any fetchable type (Row, value, or record):

let request: Request = ...
try Row.fetchCursor(db, request) // A Cursor of Row
try String.fetchAll(db, request) // [String]
try Player.fetchOne(db, request) // Player?

On top of that, a TypedRequest knows exactly what it has to do when its RowDecoder associated type can decode database rows (Row itself, values, or records):

let request = ...                // Some TypedRequest that fetches Player
try request.fetchCursor(db)      // A Cursor of Player
try request.fetchAll(db)         // [Player]
try request.fetchOne(db)         // Player?

Building Custom Requests

To build custom requests, you can create your own type that adopts the protocols, or derive requests from other requests, or use one of the built-in concrete types:

Use the asRequest(of:) method to define the type fetched by the request:

let maxScore = Player.select(max(scoreColumn))
    .asRequest(of: Int.self)
    .fetchOne(db)

extension Player {
    static func customRequest(...) -> AnyTypedRequest<Player> {
        let request = SQLRequest("SELECT ...", arguments: ...)
        return request.asRequest(of: Player.self)
    }
}

try Player.customRequest(...).fetchAll(db)   // [Player]
try Player.customRequest(...).fetchCount(db) // Int

Finally, use the adapted(_:) method to ease the consumption of complex rows with row adapters. See Joined Queries Support for more information.

Application Tools

On top of the APIs described above, GRDB provides a toolkit for applications. While none of those are mandatory, all of them help dealing with the database:

Migrations

Migrations are a convenient way to alter your database schema over time in a consistent and easy way.

Migrations run in order, once and only once. When a user upgrades your application, only non-applied migrations are run.

Inside each migration, you typically define and update your database tables according to your evolving application needs:

var migrator = DatabaseMigrator()

// v1 database
migrator.registerMigration("v1") { db in
    try db.create(table: "players") { t in ... }
    try db.create(table: "books") { t in ... }
    try db.create(index: ...)
}

// v2 database
migrator.registerMigration("v2") { db in
    try db.alter(table: "players") { t in ... }
}

// Migrations for future versions will be inserted here:
//
// // v3 database
// migrator.registerMigration("v3") { db in
//     ...
// }

Each migration runs in a separate transaction. Should one throw an error, its transaction is rollbacked, subsequent migrations do not run, and the error is eventually thrown by migrator.migrate(dbQueue).

The memory of applied migrations is stored in the database itself (in a reserved table).

You migrate the database up to the latest version with the migrate(_:) method:

try migrator.migrate(dbQueue) // or migrator.migrate(dbPool)

To migrate a database up to a specific version, use migrate(_:upTo:):

try migrator.migrate(dbQueue, upTo: "v2")

Migrations can only run forward:

try migrator.migrate(dbQueue, upTo: "v2")
try migrator.migrate(dbQueue, upTo: "v1")
// fatal error: database is already migrated beyond migration "v1"

Advanced Database Schema Changes

SQLite does not support many schema changes, and won’t let you drop a table column with ALTER TABLE … DROP COLUMN …, for example.

Yet any kind of schema change is still possible. The SQLite documentation explains in detail how to do so: https://www.sqlite.org/lang_altertable.html#otheralter. This technique requires the temporary disabling of foreign key checks, and is supported by the registerMigrationWithDeferredForeignKeyCheck function:

// Add a NOT NULL constraint on players.name:
migrator.registerMigrationWithDeferredForeignKeyCheck("AddNotNullCheckOnName") { db in
    try db.create(table: "new_players") { t in
        t.column("id", .integer).primaryKey()
        t.column("name", .text).notNull()
    }
    try db.execute("INSERT INTO new_players SELECT * FROM players")
    try db.drop(table: "players")
    try db.rename(table: "new_players", to: "players")
}

While your migration code runs with disabled foreign key checks, those are re-enabled and checked at the end of the migration, regardless of eventual errors.

Full-Text Search

Full-Text Search is an efficient way to search a corpus of textual documents.

// Create full-text tables
try db.create(virtualTable: "books", using: FTS4()) { t in // or FTS3(), or FTS5()
    t.column("author")
    t.column("title")
    t.column("body")
}

// Populate full-text table with records or SQL
try Book(...).insert(db)
try db.execute(
    "INSERT INTO books (author, title, body) VALUES (?, ?, ?)",
    arguments: [...])

// Build search patterns
let pattern = FTS3Pattern(matchingPhrase: "Moby-Dick")

// Search with the query interface or SQL
let books = try Book.matching(pattern).fetchAll(db)
let books = try Book.fetchAll(db,
    "SELECT * FROM books WHERE books MATCH ?",
    arguments: [pattern])

Choosing the Full-Text Engine

SQLite supports three full-text engines: FTS3, FTS4 and FTS5.

Generally speaking, FTS5 is better than FTS4 which improves on FTS3. But this does not really tell which engine to choose for your application. Instead, make your choice depend on:

  • The full-text features needed by the application:

    Full-Text Needs FTS3 FTS4 FTS5
    :question: Queries
    Words searches (documents that contain database) X X X
    Prefix searches (documents that contain a word starting with data) X X X
    Phrases searches (documents that contain the phrase SQLite database) X X X
    Boolean searches (documents that contain SQLite or database) X X X
    Proximity search (documents that contain SQLite near database) X X X
    :scissors: Tokenization
    Ascii case insensitivity (have DATABASE match database) X X X
    Unicode case insensitivity (have ÉLÉGANCE match élégance) X X X
    Latin diacritics insensitivity (have elegance match élégance) X X X
    English Stemming (have frustration match frustrated) X X X
    English Stemming and Ascii case insensitivity X X X
    English Stemming and Unicode case insensitivity X
    English Stemming and Latin diacritics insensitivity X
    Synonyms (have 1st match first) ¹ ¹ X ²
    Pinyin and Romaji (have romaji match ローマ字) ¹ ¹ X ²
    Stop words (don’t index, and don’t match words like and and the) ¹ ¹ X ²
    Spell checking (have alamaba match alabama) ¹ ¹ ¹
    :bowtie: Other Features
    Ranking (sort results by relevance) ¹ ¹ X
    Snippets (display a few words around a match) X X X

    ¹ Requires extra setup, possibly hard to implement.

    ² Requires a custom tokenizer.

    For a full feature list, read the SQLite documentation. Some missing features can be achieved with extra application code.

  • The speed versus disk space constraints. Roughly speaking, FTS4 and FTS5 are faster than FTS3, but use more space. FTS4 only supports content compression.

  • The location of the indexed text in your database schema. Only FTS4 and FTS5 support contentless and external content tables.

  • The SQLite library integrated in your application. The version of SQLite that ships with iOS, macOS and watchOS support FTS3 and FTS4 out of the box, but not FTS5. To use FTS5, you’ll need a custom SQLite build that activates the SQLITE_ENABLE_FTS5 compilation option.

    • See

    See FST3 vs. FTS4 and FTS5 vs. FTS3/4 for more differences.

    :point_up: Note: In case you were still wondering, it is recommended to read the SQLite documentation: FTS3 & FTS4 and FTS5.

    Create FTS3 and FTS4 Virtual Tables

    FTS3 and FTS4 full-text tables store and index textual content.

    Create tables with the create(virtualTable:using:) method:

    // CREATE VIRTUAL TABLE documents USING fts3(content)
try db.create(virtualTable: "documents", using: FTS3()) { t in
    t.column("content")
}

// CREATE VIRTUAL TABLE documents USING fts4(content)
try db.create(virtualTable: "documents", using: FTS4()) { t in
    t.column("content")
}

    All columns in a full-text table contain text. If you need to index a table that contains other kinds of values, you need an external content full-text table.

    You can specify a tokenizer:

    // CREATE VIRTUAL TABLE books USING fts4(
//   tokenize=porter,
//   author,
//   title,
//   body
// )
try db.create(virtualTable: "books", using: FTS4()) { t in
    t.tokenizer = .porter
    t.column("author")
    t.column("title")
    t.column("body")
}

    FTS4 supports options:

    // CREATE VIRTUAL TABLE books USING fts4(
//   content,
//   uuid,
//   content="",
//   compress=zip,
//   uncompress=unzip,
//   prefix="2,4",
//   notindexed=uuid,
//   languageid=lid
// )
try db.create(virtualTable: "documents", using: FTS4()) { t in
    t.content = ""
    t.compress = "zip"
    t.uncompress = "unzip"
    t.prefixes = [2, 4]
    t.column("content")
    t.column("uuid").notIndexed()
    t.column("lid").asLanguageId()
}

    The content option is involved in contentless and external content full-text tables. GRDB can help you defining full-text tables that automatically synchronize with their content table. See External Content Full-Text Tables.

    See SQLite documentation for more information.

    FTS3 and FTS4 Tokenizers

    A tokenizer defines what matching means. Depending on the tokenizer you choose, full-text searches won’t return the same results.

    SQLite ships with three built-in FTS3/4 tokenizers: simple, porter and unicode61 that use different algorithms to match queries with indexed content:

    try db.create(virtualTable: "books", using: FTS4()) { t in
    // Pick one:
    t.tokenizer = .simple // default
    t.tokenizer = .porter
    t.tokenizer = .unicode61(...)
}

    See below some examples of matches:

    content query simple porter unicode61
    Foo Foo X X X
    Foo FOO X X X
    Jérôme Jérôme X ¹ X ¹ X ¹
    Jérôme JÉRÔME X ¹
    Jérôme Jerome X ¹
    Database Databases X
    Frustration Frustrated X

    ¹ Don’t miss Unicode Full-Text Gotchas

    • simple

      try db.create(virtualTable: "books", using: FTS4()) { t in
    t.tokenizer = .simple   // default
}

      The default simple tokenizer is case-insensitive for ASCII characters. It matches foo with FOO, but not Jérôme with JÉRÔME.

      It does not provide stemming, and won’t match databases with database.

      It does not strip diacritics from latin script characters, and won’t match jérôme with jerome.

    • porter

      try db.create(virtualTable: "books", using: FTS4()) { t in
    t.tokenizer = .porter
}

      The porter tokenizer compares English words according to their roots: it matches database with databases, and frustration with frustrated.

      It does not strip diacritics from latin script characters, and won’t match jérôme with jerome.

    • unicode61

      try db.create(virtualTable: "books", using: FTS4()) { t in
    t.tokenizer = .unicode61()
    t.tokenizer = .unicode61(removeDiacritics: false)
}

      The unicode61 tokenizer is case-insensitive for unicode characters. It matches Jérôme with JÉRÔME.

      It strips diacritics from latin script characters by default, and matches jérôme with jerome. This behavior can be disabled, as in the example above.

      It does not provide stemming, and won’t match databases with database.

    See SQLite tokenizers for more information.

    FTS3Pattern

    Full-text search in FTS3 and FTS4 tables is performed with search patterns:

    • database matches all documents that contain database
    • data* matches all documents that contain a word starting with data
    • SQLite database matches all documents that contain both SQLite and database
    • SQLite OR database matches all documents that contain SQLite or database
    • "SQLite database" matches all documents that contain the SQLite database phrase

    Not all search patterns are valid: they must follow the Full-Text Index Queries Grammar.

    The FTS3Pattern type helps you validating patterns, and building valid patterns from untrusted strings (such as strings typed by users):

    struct FTS3Pattern {
    init(rawPattern: String) throws
    init?(matchingAnyTokenIn string: String)
    init?(matchingAllTokensIn string: String)
    init?(matchingPhrase string: String)
}

    The first initializer validates your raw patterns against the query grammar, and may throw a DatabaseError:

    // OK: FTS3Pattern
let pattern = try FTS3Pattern(rawPattern: "sqlite AND database")
// DatabaseError: malformed MATCH expression: [AND]
let pattern = try FTS3Pattern(rawPattern: "AND")

    The three other initializers don’t throw. They build a valid pattern from any string, including strings provided by users of your application. They let you find documents that match all given words, any given word, or a full phrase, depending on the needs of your application:

    let query = "SQLite database"
// Matches documents that contain "SQLite" or "database"
let pattern = FTS3Pattern(matchingAnyTokenIn: query)
// Matches documents that contain both "SQLite" and "database"
let pattern = FTS3Pattern(matchingAllTokensIn: query)
// Matches documents that contain "SQLite database"
let pattern = FTS3Pattern(matchingPhrase: query)

    They return nil when no pattern could be built from the input string:

    let pattern = FTS3Pattern(matchingAnyTokenIn: "")  // nil
let pattern = FTS3Pattern(matchingAnyTokenIn: "*") // nil

    FTS3Pattern are regular values. You can use them as query arguments:

    let documents = try Document.fetchAll(db,
    "SELECT * FROM documents WHERE content MATCH ?",
    arguments: [pattern])

    Use them in the query interface:

    // Search in all columns
let documents = try Document.matching(pattern).fetchAll(db)

// Search in a specific column:
let documents = try Document.filter(Column("content").match(pattern)).fetchAll(db)

    Create FTS5 Virtual Tables

    FTS5 full-text tables store and index textual content.

    To use FTS5, you’ll need a custom SQLite build that activates the SQLITE_ENABLE_FTS5 compilation option.

    Create FTS5 tables with the create(virtualTable:using:) method:

    // CREATE VIRTUAL TABLE documents USING fts5(content)
try db.create(virtualTable: "documents", using: FTS5()) { t in
    t.column("content")
}

    All columns in a full-text table contain text. If you need to index a table that contains other kinds of values, you need an external content full-text table.

    You can specify a tokenizer:

    // CREATE VIRTUAL TABLE books USING fts5(
//   tokenize='porter',
//   author,
//   title,
//   body
// )
try db.create(virtualTable: "books", using: FTS5()) { t in
    t.tokenizer = .porter()
    t.column("author")
    t.column("title")
    t.column("body")
}

    FTS5 supports options:

    // CREATE VIRTUAL TABLE books USING fts5(
//   content,
//   uuid UNINDEXED,
//   content='table',
//   content_rowid='id',
//   prefix='2 4',
//   columnsize=0,
//   detail=column
// )
try db.create(virtualTable: "documents", using: FTS5()) { t in
    t.column("content")
    t.column("uuid").notIndexed()
    t.content = "table"
    t.contentRowID = "id"
    t.prefixes = [2, 4]
    t.columnSize = 0
    t.detail = "column"
}

    The content and contentRowID options are involved in contentless and external content full-text tables. GRDB can help you defining full-text tables that automatically synchronize with their content table. See External Content Full-Text Tables.

    See SQLite documentation for more information.

    FTS5 Tokenizers

    A tokenizer defines what matching means. Depending on the tokenizer you choose, full-text searches won’t return the same results.

    SQLite ships with three built-in FTS5 tokenizers: ascii, porter and unicode61 that use different algorithms to match queries with indexed content.

    try db.create(virtualTable: "books", using: FTS5()) { t in
    // Pick one:
    t.tokenizer = .unicode61() // default
    t.tokenizer = .unicode61(...)
    t.tokenizer = .ascii
    t.tokenizer = .porter(...)
}

    See below some examples of matches:

    content query ascii unicode61 porter on ascii porter on unicode61
    Foo Foo X X X X
    Foo FOO X X X X
    Jérôme Jérôme X ¹ X ¹ X ¹ X ¹
    Jérôme JÉRÔME X ¹ X ¹
    Jérôme Jerome X ¹ X ¹
    Database Databases X X
    Frustration Frustrated X X

    ¹ Don’t miss Unicode Full-Text Gotchas

    • unicode61

      try db.create(virtualTable: "books", using: FTS5()) { t in
    t.tokenizer = .unicode61()
    t.tokenizer = .unicode61(removeDiacritics: false)
}

      The default unicode61 tokenizer is case-insensitive for unicode characters. It matches Jérôme with JÉRÔME.

      It strips diacritics from latin script characters by default, and matches jérôme with jerome. This behavior can be disabled, as in the example above.

      It does not provide stemming, and won’t match databases with database.

    • ascii

      try db.create(virtualTable: "books", using: FTS5()) { t in
    t.tokenizer = .ascii
}

      The ascii tokenizer is case-insensitive for ASCII characters. It matches foo with FOO, but not Jérôme with JÉRÔME.

      It does not provide stemming, and won’t match databases with database.

      It does not strip diacritics from latin script characters, and won’t match jérôme with jerome.

    • porter

      try db.create(virtualTable: "books", using: FTS5()) { t in
    t.tokenizer = .porter()       // porter wrapping unicode61 (the default)
    t.tokenizer = .porter(.ascii) // porter wrapping ascii
    t.tokenizer = .porter(.unicode61(removeDiacritics: false)) // porter wrapping unicode61 without diacritics stripping
}

      The porter tokenizer is a wrapper tokenizer which compares English words according to their roots: it matches database with databases, and frustration with frustrated.

      It strips diacritics from latin script characters if it wraps unicode61, and does not if it wraps ascii (see the example above).

    See SQLite tokenizers for more information, and custom FTS5 tokenizers in order to add your own tokenizers.

    FTS5Pattern

    Full-text search in FTS5 tables is performed with search patterns:

    • database matches all documents that contain database
    • data* matches all documents that contain a word starting with data
    • SQLite database matches all documents that contain both SQLite and database
    • SQLite OR database matches all documents that contain SQLite or database
    • "SQLite database" matches all documents that contain the SQLite database phrase

    Not all search patterns are valid: they must follow the Full-Text Query Syntax.

    The FTS5Pattern type helps you validating patterns, and building valid patterns from untrusted strings (such as strings typed by users):

    extension Database {
    func makeFTS5Pattern(rawPattern: String, forTable table: String) throws -> FTS5Pattern
}

struct FTS5Pattern {
    init?(matchingAnyTokenIn string: String)
    init?(matchingAllTokensIn string: String)
    init?(matchingPhrase string: String)
}

    The Database.makeFTS5Pattern(rawPattern:forTable:) method validates your raw patterns against the query grammar and the columns of the targeted table, and may throw a DatabaseError:

    // OK: FTS5Pattern
try db.makeFTS5Pattern(rawPattern: "sqlite", forTable: "books")
// DatabaseError: syntax error near \"AND\"
try db.makeFTS5Pattern(rawPattern: "AND", forTable: "books")
// DatabaseError: no such column: missing
try db.makeFTS5Pattern(rawPattern: "missing: sqlite", forTable: "books")

    The FTS5Pattern initializers don’t throw. They build a valid pattern from any string, including strings provided by users of your application. They let you find documents that match all given words, any given word, or a full phrase, depending on the needs of your application:

    let query = "SQLite database"
// Matches documents that contain "SQLite" or "database"
let pattern = FTS5Pattern(matchingAnyTokenIn: query)
// Matches documents that contain both "SQLite" and "database"
let pattern = FTS5Pattern(matchingAllTokensIn: query)
// Matches documents that contain "SQLite database"
let pattern = FTS5Pattern(matchingPhrase: query)
// Matches documents that start with "SQLite database"
let pattern = FTS5Pattern(matchingPrefixPhrase: query)

    They return nil when no pattern could be built from the input string:

    let pattern = FTS5Pattern(matchingAnyTokenIn: "")  // nil
let pattern = FTS5Pattern(matchingAnyTokenIn: "*") // nil

    FTS5Pattern are regular values. You can use them as query arguments:

    let documents = try Document.fetchAll(db,
    "SELECT * FROM documents WHERE documents MATCH ?",
    arguments: [pattern])

    Use them in the query interface:

    let documents = try Document.matching(pattern).fetchAll(db)

    FTS5: Sorting by Relevance

    FTS5 can sort results by relevance (most to least relevant):

    // SQL
let documents = try Document.fetchAll(db,
    "SELECT * FROM documents WHERE documents MATCH ? ORDER BY rank",
    arguments: [pattern])

// Query Interface
let documents = try Document.matching(pattern).order(Column.rank).fetchAll(db)

    For more information about the ranking algorithm, as well as extra options, read Sorting by Auxiliary Function Results

    GRDB does not provide any ranking for FTS3 and FTS4. See SQLite’s Search Application Tips if you really need it.

    External Content Full-Text Tables

    An external content table does not store the indexed text. Instead, it indexes the text stored in another table.

    This is very handy when you want to index a table that can not be declared as a full-text table (because it contains non-textual values, for example). You just have to define an external content full-text table that refers to the regular table.

    The two tables must be kept up-to-date, so that the full-text index matches the content of the regular table. This synchronization happens automatically if you use the synchronize(withTable:) method in your full-text table definition:

    // A regular table
try db.create(table: "books") { t in
    t.column("author", .text)
    t.column("title", .text)
    t.column("content", .text)
    ...
}

// A full-text table synchronized with the regular table
try db.create(virtualTable: "books_ft", using: FTS4()) { t in // or FTS5()
    t.synchronize(withTable: "books")
    t.column("author")
    t.column("title")
    t.column("content")
}

    The eventual content already present in the regular table is indexed, and every insert, update or delete that happens in the regular table is automatically applied to the full-text index.

    For more information, see the SQLite documentation about external content tables: FTS4, FTS5.

    See also WWDC Companion, a sample app that uses external content tables to store, display, and let the user search the WWDC sessions.

    Deleting Synchronized Full-Text Tables

    Synchronization of full-text tables with their content table happens by the mean of SQL triggers.

    SQLite automatically deletes those triggers when the content (not full-text) table is dropped.

    However, those triggers remain after the full-text table has been dropped. Unless they are dropped too, they will prevent future insertion, updates, and deletions in the content table, and the creation of a new full-text table.

    To drop those triggers, use the dropFTS4SynchronizationTriggers or dropFTS5SynchronizationTriggers methods:

    // Create tables
try db.create(table: "books") { t in
    ...
}
try db.create(virtualTable: "books_ft", using: FTS4()) { t in
    t.synchronize(withTable: "books")
    ...
}

// Drop full-text table
try db.drop(table: "books_ft")
try db.dropFTS4SynchronizationTriggers(forTable: "books_ft")

    :warning: Warning: there was a bug in GRDB up to version 2.3.1 included, which created triggers with a wrong name. If it is possible that the full-text table was created by an old version of GRDB, then delete the synchronization triggers twice: once with the name of the deleted full-text table, and once with the name of the content table:

    // Drop full-text table
try db.drop(table: "books_ft")
try db.dropFTS4SynchronizationTriggers(forTable: "books_ft")
try db.dropFTS4SynchronizationTriggers(forTable: "books") // Support for GRDB <= 2.3.1

    Querying External Content Full-Text Tables

    When you need to perform a full-text search, and the external content table contains all the data you need, you can simply query the full-text table.

    But if you need to load columns from the regular table, and in the same time perform a full-text search, then you will need to query both tables at the same time.

    That is because SQLite will throw an error when you try to perform a full-text search on a regular table:

    // SQLite error 1: unable to use function MATCH in the requested context
// SELECT * FROM books WHERE books MATCH '...'
let books = Book.matching(pattern).fetchAll(db)

    The solution is to perform a joined request, using raw SQL:

    let sql = """
    SELECT books.*
    FROM books
    JOIN books_ft ON
    books_ft.rowid = books.rowid AND
    books_ft MATCH ?
    """
let books = Book.fetchAll(db, sql, arguments: [pattern])

    Full-Text Records

    You can define record types around the full-text virtual tables.

    However these tables don’t have any explicit primary key. Instead, they use the implicit rowid primary key: a special hidden column named rowid.

    You will have to expose this hidden column in order to fetch, delete, and update full-text records by primary key.

    Unicode Full-Text Gotchas

    The SQLite built-in tokenizers for FTS3, FTS4 and FTS5 are generally unicode-aware, with a few caveats, and limitations.

    Generally speaking, matches may fail when content and query don’t use the same unicode normalization. SQLite actually exhibits inconsistent behavior in this regard.

    For example, for aimé to match aimé, they better have the same normalization: the NFC aim\u{00E9} form may not match its NFD aime\u{0301} equivalent. Most strings that you get from Swift, UIKit and Cocoa use NFC, so be careful with NFD inputs (such as strings from the HFS+ file system, or strings that you can’t trust like network inputs). Use String.precomposedStringWithCanonicalMapping to turn a string into NFC.

    Besides, if you want fi to match the ligature fi (U+FB01), then you need to normalize your indexed contents and inputs to NFKC or NFKD. Use String.precomposedStringWithCompatibilityMapping to turn a string into NFKC.

    Unicode normalization is not the end of the story, because it won’t help Encyclopaedia match Encyclopædia, Mueller, Müller, Grossmann, Großmann, or Diyarbakır, DIYARBAKIR. The String.applyingTransform method can help.

    GRDB lets you write custom FTS5 tokenizers that can transparently deal with all these issues. For FTS3 and FTS4, you’ll need to pre-process your strings before injecting them in the full-text engine.

    Happy indexing!

    Joined Queries Support

    GRDB helps consuming joined queries with complex selection.

    In this chapter, we will focus on the extraction of information from complex rows, such as the ones fetched by the query below:

    -- How to consume the left, middle, and right parts of those rows?
SELECT players.*, teams.*, MAX(rounds.score) AS maxScore
FROM players
LEFT JOIN teams ON ...
LEFT JOIN rounds ON ...
GROUP BY ...

    We will not talk about building joined queries.

    So what are we talking about?

    It is difficult to consume rows fetched from complex joined queries, because they often contain several columns with the same name: id from table players, id from table teams, etc.

    When such ambiguity happens, GRDB row accessors always favor the leftmost matching column. This means that row["id"] would give a player id, whithout any obvious way to access the team id.

    A classical technique to avoid this ambiguity is to give each column a unique name. For example:

    -- A classical technique
SELECT players.id AS players_id, players.name AS players_name, teams.id AS teams_id, teams.name AS teams_name, teams.color AS teams_color, MAX(rounds.score) AS maxScore
FROM players
LEFT JOIN teams ON ...
LEFT JOIN rounds ON ...
GROUP BY ...

    This technique works pretty well, but it has three drawbacks:

    1. The selection becomes hard to read and understand.
    2. Such queries are difficult to write by hand.
    3. The mangled names are a very bad fit for RowConvertible records that expect specific column names. After all, if the Team record type can read SELECT * FROM teams ..., it should be able to read SELECT ..., teams.*, ... as well.

    We thus need another technique. Below we’ll see how to split rows into slices, and preserve column names.

    SELECT players.*, teams.*, MAX(rounds.score) AS maxScore FROM ... will be splitted into three slices: one that contains player’s columns, one that contains team’s columns, and a remaining slice that contains remaining column(s). The Player record type will be able to read the first slice, which contains the colums expected by the Player.init(row:) initializer. In the same way, the Team record type could read the second slice.

    Unlike the name-mangling technique, splitting rows keeps SQL legible, accepts your hand-crafted SQL queries, and plays as nicely as possible with your existing record types.

    Splitting Rows, an Introduction

    Let’s first write some introductory code, hoping that this chapter will make you understand how pieces fall together. We’ll see later how records will help us streamline the initial approach, how to track changes in joined requests, and how we can use the standard Decodable protocol.

    To split rows, we will use row adapters. Row adapters adapt rows so that row consumers see exactly the columns they want. Among other things, row adapters can define several row scopes that give access to as many row slices. Sounds like a perfect match.

    At the very beginning, there is an SQL query:

    try dbQueue.inDatabase { db in
    let sql = """
        SELECT players.*, teams.*, MAX(rounds.score) AS maxScore
        FROM players
        LEFT JOIN teams ON ...
        LEFT JOIN rounds ON ...
        GROUP BY ...
        """

    We need an adapter that extracts players’ columns, in a slice that has as many columns as there are columns in the players table. That’s RangeRowAdapter:

        // SELECT players.*, teams.*, ...
    //        <------->
    let playersWidth = try db.columns(in: "players").count
    let playerAdapter = RangeRowAdapter(0 ..< playersWidth)

    We also need an adapter that extracts teams’ columns:

        // SELECT players.*, teams.*, ...
    //                   <----->
    let teamsWidth = try db.columns(in: "teams").count
    let teamAdapter = RangeRowAdapter(playersWidth ..< (playersWidth + teamsWidth))

    We merge those two adapters in a single ScopeAdapter that will allow us to access both sliced rows:

        let playerScope = "player"
    let teamScope = "team"
    let adapter = ScopeAdapter([
        playerScope: playerAdapter,
        teamScope: teamAdapter])

    And now we can fetch, and start consuming our rows. You already know row cursors:

        let rows = try Row.fetchCursor(db, sql, adapter: adapter)
    while let row = try rows.next() {

    From a fetched row, we can build a player:

            let player: Player = row[playerScope]

    In the SQL query, the team is joined with the LEFT JOIN operator. This means that the team may be missing: its slice may contain team values, or it may only contain NULLs. When this happens, we don’t want to build a Team record, and we thus load an optional Team:

            let team: Team? = row[teamScope]

    And finally, we can load the maximum score, assuming that the maxScore column is not ambiguous:

            let maxScore: Int = row["maxScore"]

        print("player: \(player)")
        print("team: \(team)")
        print("maxScore: \(maxScore)")
    }
}

    :bulb: In this chapter, we have learned:

    • how to use RangeRowAdapter to extract a specific table’s columns into a row slice.
    • how to use ScopeAdapter to gives access to several row slices through named scopes.
    • how to use Row subscripting to extract records from rows, or optional records in order to deal with left joins.

    Splitting Rows, the Record Way

    Our introduction above has introduced important techniques. It uses row adapters in order to split rows. It uses Row subscripting in order to extract records from row slices.

    But we may want to make it more usable and robust:

    1. It’s generally easier to consume records than raw rows.
    2. Joined records not always need all columns from a table (see TableMapping.databaseSelection in Columns Selected by a Request).
    3. Building row adapters is long and error prone.

    To address the first bullet, let’s define a record that holds our player, optional team, and maximum score. Since it can decode database rows, it adopts the RowConvertible protocol:

    struct Item {
    var player: Player
    var team: Team?
    var maxScore: Int
}

/// Item can decode rows:
extension Item: RowConvertible {
    private enum Scopes {
        static let player = "player"
        static let team = "team"
    }

    init(row: Row) {
        player = row[Scopes.player]
        team = row[Scopes.team]
        maxScore = row["maxScore"]
    }
}

    Let’s now write the method that fetches items:

    extension Item {
    static func fetchAll(_ db: Database) throws -> [Item] {

    To acknowledge that both Player and Team records may customize their selection of the players and teams columns, we’ll write our SQL in a slightly different way:

            // Let Player and Team customize their selection:
        let sql = """
            SELECT
                \(Player.selectionSQL()), -- instead of players.*
                \(Team.selectionSQL()),   -- instead of teams.*
                MAX(rounds.score) AS maxScore
            FROM players
            LEFT JOIN teams ON ...
            LEFT JOIN rounds ON ...
            GROUP BY ...
            """

    Player.selectionSQL() will output players.*, unless Player defines a customized selection.

    :point_up: Note: you may also provide an alias: SELECT \(Players.selectionSQL(alias: "p")) FROM players p ...

    Now is the time to build adapters (taking in account the customized selection of both players and teams). We use the splittingRowAdapters global function, which builds row adapters of desired widths:

            let adapters = try splittingRowAdapters(columnCounts: [
            Player.numberOfSelectedColumns(db),
            Team.numberOfSelectedColumns(db)])

        let adapter = ScopeAdapter([
            Scopes.player: adapters[0],
            Scopes.team: adapters[1]])

    :point_up: Note: splittingRowAdapters returns as many adapters as necessary to fully split a row. In the example above, it returns three adapters: one for players, one for teams, and one for the remaining columns.

    And finally, we can fetch items:

            return try Item.fetchAll(db, sql, adapter: adapter)
    }
}

    And when your app needs to fetch items, it now reads:

    // Fetch items
let items = try dbQueue.inDatabase { db in
    try Item.fetchAll(db)
}

    :bulb: In this chapter, we have learned:

    • how to define a RowConvertible record that consumes rows fetched from a joined query.
    • how to use selectionSQL and numberOfSelectedColumns in order to deal with nested record types that define custom selection.
    • how to use splittingRowAdapters in order to streamline the definition of row slices.
    • how to gather all relevant methods and constants in a record type, fully responsible of its relationship with the database.

    Splitting Rows, the Request Way

    The Item.fetchAll method above directly fetches records. It’s all good, but in order to profit from database observation with FetchedRecordsController or RxGRDB, you’ll need a custom request that defines a database query.

    It is recommended that your read the previous paragraphs before you dive in this sample code. We start with the same Item record as above:

    struct Item {
    var player: Player
    var team: Team?
    var maxScore: Int
}

/// Item can decode rows:
extension Item: RowConvertible {
    private enum Scopes {
        static let player = "player"
        static let team = "team"
    }

    init(row: Row) {
        player = row[Scopes.player]
        team = row[Scopes.team]
        maxScore = row["maxScore"]
    }
}

    Now we write a method that returns a request, and build the fetching method on top of that request:

    extension Item {
    /// The request for all items
    static func all() -> AnyTypedRequest<Item> {
        let sql = """
            SELECT
                \(Player.selectionSQL()),
                \(Team.selectionSQL()),
                MAX(rounds.score) AS maxScore
            FROM players
            LEFT JOIN teams ON ...
            LEFT JOIN rounds ON ...
            GROUP BY ...
            """
        return SQLRequest(sql).adapted { db in
            let adapters = try splittingRowAdapters(columnCounts: [
                Player.numberOfSelectedColumns(db),
                Team.numberOfSelectedColumns(db)])
            return ScopeAdapter([
                Scopes.player: adapters[0],
                Scopes.team: adapters[1]])
            }
            .asRequest(of: Item.self)
    }

    /// Fetches all items
    static func fetchAll(_ db: Database) throws -> [Item] {
        return try all().fetchAll(db)
    }
}

    It is now time to use our request:

    // Fetch items
let items = try dbQueue.inDatabase { db in
    try Item.fetchAll(db)
}

// Track items with RxRGDB:
Item.all()
    .rx.fetchAll(in: dbQueue)
    .subscribe(onNext: { items: [Item] in
        print("items have changed")
    })

    :bulb: In this chapter, we have learned how to define a custom request that can both fetch records from joined queries, and feed database observation tools.

    Splitting Rows, the Codable Way

    Codable Records build on top of the standard Decodable protocol in order to decode database rows.

    You can consume complex joined queries with Codable records as well. As a demonstration, we’ll rewrite the above sample code:

    struct Player: Decodable, RowConvertible, TableMapping {
    static let databaseTableName = "players"
    var id: Int64
    var name: String
}
struct Team: Decodable, RowConvertible, TableMapping {
    static let databaseTableName = "teams"
    var id: Int64
    var name: String
    var color: Color
}
struct Item: Decodable, RowConvertible {
    var player: Player
    var team: Team?
    var maxScore: Int
}

extension Item {
    /// The request for all items
    static func all() -> AnyTypedRequest<Item> {
        let sql = """
            SELECT
                \(Player.selectionSQL()),
                \(Team.selectionSQL()),
                MAX(rounds.score) AS maxScore
            FROM players
            LEFT JOIN teams ON ...
            LEFT JOIN rounds ON ...
            GROUP BY ...
            """
        return SQLRequest(sql).adapted { db in
            let adapters = try splittingRowAdapters(columnCounts: [
                Player.numberOfSelectedColumns(db),
                Team.numberOfSelectedColumns(db)])
            return ScopeAdapter([
                CodingKeys.player.stringValue: adapters[0],
                CodingKeys.team.stringValue: adapters[1]])
            }
            .asRequest(of: Item.self)
    }

    /// Fetches all items
    static func fetchAll(_ db: Database) throws -> [Item] {
        return try all().fetchAll(db)
    }
}

// Fetch items
let items = try dbQueue.inDatabase { db in
    try Item.fetchAll(db)
}

// Track items with RxRGDB:
Item.all()
    .rx.fetchAll(in: dbQueue)
    .subscribe(onNext: { items: [Item] in
        print("items have changed")
    })

    :bulb: In this chapter, we have learned how to use the Decodable protocol and its associated CodingKeys enum in order to dry up our code.

    Database Changes Observation

    SQLite notifies its host application of changes performed to the database, as well of transaction commits and rollbacks.

    GRDB puts this SQLite feature to some good use, and lets you observe the database in various ways:

    Database observation requires that a single database queue or pool is kept open for all the duration of the database usage.

    After Commit Hook

    When your application needs to make sure a database transaction has been successfully committed before it executes some work, use the Database.afterNextTransactionCommit(_:) method.

    Its closure argument is called right after database changes have been successfully written to disk:

    dbQueue.inTransaction { db in
    db.afterNextTransactionCommit { db in
        print("success")
    }
    ...
    return .commit // prints "success"
}

    The closure runs in a protected dispatch queue, serialized with all database updates.

    This after commit hook helps synchronizing the database with other resources, such as files, or system sensors.

    In the example below, a location manager starts monitoring a CLRegion if and only if it has successfully been stored in the database:

    /// Inserts a region in the database, and start monitoring upon
/// successful insertion.
func startMonitoring(_ db: Database, region: CLRegion) throws {
    // Make sure database is inside a transaction
    try db.inSavepoint {

        // Save the region in the database
        try insert(...)

        // Start monitoring if and only if the insertion is
        // eventually committed
        db.afterNextTransactionCommit { _ in
            // locationManager prefers the main queue:
            DispatchQueue.main.async {
                locationManager.startMonitoring(for: region)
            }
        }

        return .commit
    }
}

    The method above won’t trigger the location manager if the transaction is eventually rollbacked (explicitely, or because of an error), as in the sample code below:

    try dbQueue.inTransaction { db in
    // success
    try startMonitoring(db, region)

    // On error, the transaction is rollbacked, the region is not inserted, and
    // the location manager is not invoked.
    try failableMethod(db)

    return .commit
}

    TransactionObserver Protocol

    The TransactionObserver protocol lets you observe database changes and transactions:

    protocol TransactionObserver : class {
    /// Filters database changes that should be notified the the
    /// `databaseDidChange(with:)` method.
    func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool

    /// Notifies a database change:
    /// - event.kind (insert, update, or delete)
    /// - event.tableName
    /// - event.rowID
    ///
    /// For performance reasons, the event is only valid for the duration of
    /// this method call. If you need to keep it longer, store a copy:
    /// event.copy().
    func databaseDidChange(with event: DatabaseEvent)

    /// An opportunity to rollback pending changes by throwing an error.
    func databaseWillCommit() throws

    /// Database changes have been committed.
    func databaseDidCommit(_ db: Database)

    /// Database changes have been rollbacked.
    func databaseDidRollback(_ db: Database)
}

    Activate a Transaction Observer

    To activate a transaction observer, add it to the database queue or pool:

    let observer = MyObserver()
dbQueue.add(transactionObserver: observer)

    By default, database holds weak references to its transaction observers: they are not retained, and stop getting notifications after they are deallocated. See Observation Extent for more options.

    Database Changes And Transactions

    A transaction observer is notified of all database changes: inserts, updates and deletes. This includes indirect changes triggered by ON DELETE and ON UPDATE actions associated to foreign keys.

    :point_up: Note: the changes that are not notified are changes to internal system tables (such as sqlite_master), changes to WITHOUT ROWID tables, and the deletion of duplicate rows triggered by ON CONFLICT REPLACE clauses (this last exception might change in a future release of SQLite).

    Notified changes are not actually written to disk until databaseDidCommit is called. On the other side, databaseDidRollback confirms their invalidation:

    try dbQueue.inTransaction { db in
    try db.execute("INSERT ...") // 1. didChange
    try db.execute("UPDATE ...") // 2. didChange
    return .commit               // 3. willCommit, 4. didCommit
}

try dbQueue.inTransaction { db in
    try db.execute("INSERT ...") // 1. didChange
    try db.execute("UPDATE ...") // 2. didChange
    return .rollback             // 3. didRollback
}

    Database statements that are executed outside of an explicit transaction do not drop off the radar:

    try dbQueue.inDatabase { db in
    try db.execute("INSERT ...") // 1. didChange, 2. willCommit, 3. didCommit
    try db.execute("UPDATE ...") // 4. didChange, 5. willCommit, 6. didCommit
}

    Changes that are on hold because of a savepoint are only notified after the savepoint has been released. This makes sure that notified events are only events that have an opportunity to be committed:

    try dbQueue.inTransaction { db in
    try db.execute("INSERT ...")            // 1. didChange

    try db.execute("SAVEPOINT foo")
    try db.execute("UPDATE ...")            // delayed
    try db.execute("UPDATE ...")            // delayed
    try db.execute("RELEASE SAVEPOINT foo") // 2. didChange, 3. didChange

    try db.execute("SAVEPOINT foo")
    try db.execute("UPDATE ...")            // not notified
    try db.execute("ROLLBACK TO SAVEPOINT foo")

    return .commit                          // 4. willCommit, 5. didCommit
}

    Eventual errors thrown from databaseWillCommit are exposed to the application code:

    do {
    try dbQueue.inTransaction { db in
        ...
        return .commit           // 1. willCommit (throws), 2. didRollback
    }
} catch {
    // 3. The error thrown by the transaction observer.
}

    :point_up: Note: all callbacks are called in a protected dispatch queue, and serialized with all database updates.

    :point_up: Note: the databaseDidChange(with:) and databaseWillCommit() callbacks must not touch the SQLite database. This limitation does not apply to databaseDidCommit and databaseDidRollback which can use their database argument.

    FetchedRecordsController and RxGRDB are based on the TransactionObserver protocol.

    See also TableChangeObserver.swift, which shows a transaction observer that notifies of modified database tables with NSNotificationCenter.

    Filtering Database Events

    Transaction observers can avoid being notified of database changes they are not interested in.

    The filtering happens in the observes(eventsOfKind:) method, which tells whether the observer wants notification of specific kinds of changes, or not. For example, here is how an observer can focus on the changes that happen on the players database table:

    class PlayerObserver: TransactionObserver {
    func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool {
        // Only observe changes to the "players" table.
        return eventKind.tableName == "players"
    }

    func databaseDidChange(with event: DatabaseEvent) {
        // This method is only called for changes that happen to
        // the "players" table.
    }
}

    Generally speaking, the observes(eventsOfKind:) method can distinguish insertions from deletions and updates, and is also able to inspect the columns that are about to be changed:

    class PlayerScoreObserver: TransactionObserver {
    func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool {
        // Only observe changes to the "score" column of the "players" table.
        switch eventKind {
        case .insert(let tableName):
            return tableName == "players"
        case .delete(let tableName):
            return tableName == "players"
        case .update(let tableName, let columnNames):
            return tableName == "players" && columnNames.contains("score")
        }
    }
}

    When the observes(eventsOfKind:) method returns false for all event kinds, the observer is still notified of commits and rollbacks:

    class PureTransactionObserver: TransactionObserver {
    func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool {
        // Ignore all individual changes
        return false
    }

    func databaseDidChange(with event: DatabaseEvent) { /* Never called */ }
    func databaseWillCommit() throws { /* Called before commit */ }
    func databaseDidRollback(_ db: Database) { /* Called on rollback */ }
    func databaseDidCommit(_ db: Database) { /* Called on commit */ }
}

    Observation Extent

    You can specify how long an observer is notified of database changes and transactions.

    The remove(transactionObserver:) method explicitely stops notifications, at any time:

    // From a database queue or pool:
dbQueue.remove(transactionObserver: observer)

// From a database connection:
dbQueue.inDatabase { db in // or dbPool.write
    db.remove(transactionObserver: observer)
}

    Alternatively, use the extent parameter of the add(transactionObserver:extent:) method:

    let observer = MyObserver()

// On a database queue or pool:
dbQueue.add(transactionObserver: observer) // default extent
dbQueue.add(transactionObserver: observer, extent: .observerLifetime)
dbQueue.add(transactionObserver: observer, extent: .nextTransaction)
dbQueue.add(transactionObserver: observer, extent: .databaseLifetime)

// On a database connection:
dbQueue.inDatabase { db in
    db.add(transactionObserver: ...)
}

    • The default extent is .observerLifetime: the database holds a weak reference to the observer, and the observation automatically ends when the observer is deallocated. Meanwhile, observer is notified of all changes and transactions.

    • .nextTransaction activates the observer until the current or next transaction completes. The database keeps a strong reference to the observer until its databaseDidCommit or databaseDidRollback method is eventually called. Hereafter the observer won’t get any further notification.

    • .databaseLifetime has the database retain and notify the observer until the database connection is closed.

    Finally, an observer may ignore all database changes until the end of the current transaction:

    class PlayerObserver: TransactionObserver {
    var playersTableWasModified = false

    func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool {
        return eventKind.tableName == "players"
    }

    func databaseDidChange(with event: DatabaseEvent) {
        playersTableWasModified = true

        // It is pointless to keep on tracking further changes:
        stopObservingDatabaseChangesUntilNextTransaction()
    }
}

    After stopObservingDatabaseChangesUntilNextTransaction(), the databaseDidChange(with:) method will not be notified of any change for the remaining duration of the current transaction. This helps GRDB optimize database observation.

    Support for SQLite Pre-Update Hooks

    A custom SQLite build can activate SQLite preupdate hooks. In this case, TransactionObserverType gets an extra callback which lets you observe individual column values in the rows modified by a transaction:

    protocol TransactionObserverType : class {
    #if SQLITE_ENABLE_PREUPDATE_HOOK
    /// Notifies before a database change (insert, update, or delete)
    /// with change information (initial / final values for the row's
    /// columns).
    ///
    /// The event is only valid for the duration of this method call. If you
    /// need to keep it longer, store a copy: event.copy().
    func databaseWillChange(with event: DatabasePreUpdateEvent)
    #endif
}

    FetchedRecordsController

    You use FetchedRecordsController to track changes in the results of an SQLite request.

    FetchedRecordsController can also feed table views, collection views, and animate cells when the results of the request change.

    It looks and behaves very much like Core Data’s NSFetchedResultsController.

    Given a fetch request, and a type that adopts the RowConvertible protocol, such as a subclass of the Record class, a FetchedRecordsController is able to track changes in the results of the fetch request, notify of those changes, and return the results of the request in a form that is suitable for a table view or a collection view, with one cell per fetched record.

    See GRDBDemoiOS for an sample app that uses FetchedRecordsController.

    See also RxGRDB, an RxSwift extension, for a reactive way to track request changes.

    Creating the Fetched Records Controller

    When you initialize a fetched records controller, you provide the following mandatory information:

    class Player : Record { ... }
let dbQueue = DatabaseQueue(...)    // Or DatabasePool

// Using a Request from the Query Interface:
let controller = FetchedRecordsController(
    dbQueue,
    request: Player.order(Column("name")))

// Using SQL, and eventual arguments:
let controller = FetchedRecordsController<Player>(
    dbQueue,
    sql: "SELECT * FROM players ORDER BY name WHERE countryIsoCode = ?",
    arguments: ["FR"])

    The fetch request can involve several database tables. The fetched records controller will only track changes in the columns and tables used by the fetch request.

    let controller = FetchedRecordsController<Player>(
    dbQueue,
    sql: """
        SELECT players.name, COUNT(books.id) AS bookCount
        FROM players
        LEFT JOIN books ON books.authorId = players.id
        GROUP BY players.id
        ORDER BY players.name
        """)

    After creating an instance, you invoke performFetch() to actually execute the fetch.

    try controller.performFetch()

    Responding to Changes

    In general, FetchedRecordsController is designed to respond to changes at the database layer, by notifying when database rows change location or values.

    Changes are not reflected until they are applied in the database by a successful transaction. Transactions can be explicit, or implicit:

    try dbQueue.inTransaction { db in
    try player1.insert(db)
    try player2.insert(db)
    return .commit         // Explicit transaction
}

try dbQueue.inDatabase { db in
    try player1.insert(db) // Implicit transaction
    try player2.insert(db) // Implicit transaction
}

    When you apply several changes to the database, you should group them in a single explicit transaction. The controller will then notify of all changes together.

    The Changes Notifications

    An instance of FetchedRecordsController notifies that the controller’s fetched records have been changed by the mean of callbacks:

    let controller = try FetchedRecordsController(...)

controller.trackChanges(
    // controller's records are about to change:
    willChange: { controller in ... },

    // notification of individual record changes:
    onChange: { (controller, record, change) in ... },

    // controller's records have changed:
    didChange: { controller in ... })

try controller.performFetch()

    See Implementing Table View Updates for more detail on table view updates.

    All callbacks are optional. When you only need to grab the latest results, you can omit the didChange argument name:

    controller.trackChanges { controller in
    let newPlayers = controller.fetchedRecords // [Player]
}

    :warning: Warning: notification of individual record changes (the onChange callback) has FetchedRecordsController use a diffing algorithm that has a high complexity, a high memory consumption, and is thus not suited for large result sets. One hundred rows is probably OK, but one thousand is probably not. If your application experiences problems with large lists, see Issue 263 for more information.

    Callbacks have the fetched record controller itself as an argument: use it in order to avoid memory leaks:

    // BAD: memory leak
controller.trackChanges { _ in
    let newPlayers = controller.fetchedRecords
}

// GOOD
controller.trackChanges { controller in
    let newPlayers = controller.fetchedRecords
}

    Callbacks are invoked asynchronously. See FetchedRecordsController Concurrency for more information.

    Values fetched from inside callbacks may be inconsistent with the controller’s records. This is because after database has changed, and before the controller had the opportunity to invoke callbacks in the main thread, other database changes can happen.

    To avoid inconsistencies, provide a fetchAlongside argument to the trackChanges method, as below:

    controller.trackChanges(
    fetchAlongside: { db in
        // Fetch any extra value, for example the number of fetched records:
        return try Player.fetchCount(db)
    },
    didChange: { (controller, count) in
        // The extra value is the second argument.
        let recordsCount = controller.fetchedRecords.count
        assert(count == recordsCount) // guaranteed
    })

    Whenever the fetched records controller can not look for changes after a transaction has potentially modified the tracked request, an error handler is called. The request observation is not stopped, though: future transactions may successfully be handled, and the notified changes will then be based on the last successful fetch.

    controller.trackErrors { (controller, error) in
    print("Missed a transaction because \(error)")
}

    Modifying the Fetch Request

    You can change a fetched records controller’s fetch request or SQL query.

    controller.setRequest(Player.order(Column("name")))
controller.setRequest(sql: "SELECT ...", arguments: ...)

    The notification callbacks are notified of eventual changes if the new request fetches a different set of records.

    :point_up: Note: This behavior differs from Core Data’s NSFetchedResultsController, which does not notify of record changes when the fetch request is replaced.

    Change callbacks are invoked asynchronously. This means that modifying the request from the main thread does not immediately triggers callbacks. When you need to take immediate action, force the controller to refresh immediately with its performFetch method. In this case, changes callbacks are not called:

    // Change request on the main thread:
controller.setRequest(Player.order(Column("name")))
// Here callbacks have not been called yet.
// You can cancel them, and refresh records immediately:
try controller.performFetch()

    Table and Collection Views

    FetchedRecordsController let you feed table and collection views, and keep them up-to-date with the database content.

    For nice animated updates, a fetched records controller needs to recognize identical records between two different result sets. When records adopt the TableMapping protocol, they are automatically compared according to their primary key:

    class Player : TableMapping { ... }
let controller = FetchedRecordsController(
    dbQueue,
    request: Player.all())

    For other types, the fetched records controller needs you to be more explicit:

    let controller = FetchedRecordsController(
    dbQueue,
    request: ...,
    isSameRecord: { (player1, player2) in player1.id == player2.id })

    Implementing the Table View Datasource Methods

    The table view data source asks the fetched records controller to provide relevant information:

    func numberOfSections(in tableView: UITableView) -> Int {
    return fetchedRecordsController.sections.count
}

func tableView(_ tableView: UITableView, numberOfRowsInSection section: Int) -> Int {
    return fetchedRecordsController.sections[section].numberOfRecords
}

func tableView(_ tableView: UITableView, cellForRowAt indexPath: IndexPath) -> UITableViewCell {
    let cell = ...
    let record = fetchedRecordsController.record(at: indexPath)
    // Configure the cell
    return cell
}

    :point_up: Note: In its current state, FetchedRecordsController does not support grouping table view rows into custom sections: it generates a unique section.

    Implementing Table View Updates

    When changes in the fetched records should reload the whole table view, you can simply tell so:

    controller.trackChanges { [unowned self] _ in
    self.tableView.reloadData()
}

    Yet, FetchedRecordsController can notify that the controller’s fetched records have been changed due to some add, remove, move, or update operations, and help applying animated changes to a UITableView.

    Typical Table View Updates

    For animated table view updates, use the willChange and didChange callbacks to bracket events provided by the fetched records controller, as illustrated in the following example:

    // Assume self has a tableView property, and a cell configuration
// method named configure(_:at:).

controller.trackChanges(
    // controller's records are about to change:
    willChange: { [unowned self] _ in
        self.tableView.beginUpdates()
    },

    // notification of individual record changes:
    onChange: { [unowned self] (controller, record, change) in
        switch change {
        case .insertion(let indexPath):
            self.tableView.insertRows(at: [indexPath], with: .fade)

        case .deletion(let indexPath):
            self.tableView.deleteRows(at: [indexPath], with: .fade)

        case .update(let indexPath, _):
            if let cell = self.tableView.cellForRow(at: indexPath) {
                self.configure(cell, at: indexPath)
            }

        case .move(let indexPath, let newIndexPath, _):
            self.tableView.deleteRows(at: [indexPath], with: .fade)
            self.tableView.insertRows(at: [newIndexPath], with: .fade)

            // // Alternate technique which actually moves cells around:
            // let cell = self.tableView.cellForRow(at: indexPath)
            // self.tableView.moveRow(at: indexPath, to: newIndexPath)
            // if let cell = cell {
            //     self.configure(cell, at: newIndexPath)
            // }
        }
    },

    // controller's records have changed:
    didChange: { [unowned self] _ in
        self.tableView.endUpdates()
    })

    :warning: Warning: notification of individual record changes (the onChange callback) has FetchedRecordsController use a diffing algorithm that has a high complexity, a high memory consumption, and is thus not suited for large result sets. One hundred rows is probably OK, but one thousand is probably not. If your application experiences problems with large lists, see Issue 263 for more information.

    See GRDBDemoiOS for an sample app that uses FetchedRecordsController to animate a table view.

    :point_up: Note: our sample code above uses unowned references to the table view controller. This is a safe pattern as long as the table view controller owns the fetched records controller, and is deallocated from the main thread (this is usually the case). In other situations, prefer weak references.

    FetchedRecordsController Concurrency

    A fetched records controller can not be used from any thread.

    When the database itself can be read and modified from any thread, fetched records controllers must be used from the main thread. Record changes are also notified on the main thread.

    Change callbacks are invoked asynchronously. This means that changes made from the main thread are not immediately notified. When you need to take immediate action, force the controller to refresh immediately with its performFetch method. In this case, changes callbacks are not called:

    // Change database on the main thread:
try dbQueue.inDatabase { db in
    try Player(...).insert(db)
}
// Here callbacks have not been called yet.
// You can cancel them, and refresh records immediately:
try controller.performFetch()

    :point_up: Note: when the main thread does not fit your needs, give a serial dispatch queue to the controller initializer: the controller must then be used from this queue, and record changes are notified on this queue as well.

    let queue = DispatchQueue()
queue.async {
    let controller = try FetchedRecordsController(..., queue: queue)
    controller.trackChanges { /* in queue */ }
    try controller.performFetch()
}

    Encryption

    GRDB can encrypt your database with SQLCipher v3.4.1.

    You can use CocoaPods (version 1.2 or higher), and specify in your Podfile:

    use_frameworks!
pod 'GRDBCipher'

    Alternatively, perform a manual installation of GRDB and SQLCipher:

    1. Clone the GRDB git repository, checkout the latest tagged version, and download SQLCipher sources:

      cd [GRDB directory]
git checkout v2.9.0
git submodule update --init SQLCipher/src

    2. Embed the GRDBCipher.xcodeproj project in your own project.

    3. Add the GRDBCipherOSX or GRDBCipheriOS target in the Target Dependencies section of the Build Phases tab of your application target.

    4. Add the GRDBCipher.framework from the targetted platform to the Embedded Binaries section of the General tab of your target.

    You create and open an encrypted database by providing a passphrase to your database connection:

    import GRDBCipher

var configuration = Configuration()
configuration.passphrase = "secret"
let dbQueue = try DatabaseQueue(path: "...", configuration: configuration)

    You can change the passphrase of an already encrypted database:

    try dbQueue.change(passphrase: "newSecret")

    Providing a passphrase won’t encrypt a clear-text database that already exists, though. SQLCipher can’t do that, and you will get an error instead: SQLite error 26: file is encrypted or is not a database.

    To encrypt an existing clear-text database, create a new and empty encrypted database, and copy the content of the clear-text database in it. The technique to do that is documented by SQLCipher. With GRDB, it gives:

    // The clear-text database
let clearDBQueue = try DatabaseQueue(path: "/path/to/clear.db")

// The encrypted database, at some distinct location:
var configuration = Configuration()
configuration.passphrase = "secret"
let encryptedDBQueue = try DatabaseQueue(path: "/path/to/encrypted.db", configuration: config)

try clearDBQueue.inDatabase { db in
    try db.execute("ATTACH DATABASE ? AS encrypted KEY ?", arguments: [encryptedDBQueue.path, "secret"])
    try db.execute("SELECT sqlcipher_export('encrypted')")
    try db.execute("DETACH DATABASE encrypted")
}

// Now the copy is done, and the clear-text database can be deleted.

    Backup

    You can backup (copy) a database into another.

    Backups can for example help you copying an in-memory database to and from a database file when you implement NSDocument subclasses.

    let source: DatabaseQueue = ...      // or DatabasePool
let destination: DatabaseQueue = ... // or DatabasePool
try source.backup(to: destination)

    The backup method blocks the current thread until the destination database contains the same contents as the source database.

    When the source is a database pool, concurrent writes can happen during the backup. Those writes may, or may not, be reflected in the backup, but they won’t trigger any error.

    Good To Know

    This chapter covers general topics that you should be aware of.

    Avoiding SQL Injection

    SQL injection is a technique that lets an attacker nuke your database.

    XKCD: Exploits of a Mom

    https://xkcd.com/327/

    Here is an example of code that is vulnerable to SQL injection:

    // BAD BAD BAD
let name = textField.text
try dbQueue.inDatabase { db in
    try db.execute("UPDATE students SET name = '\(name)' WHERE id = \(id)")
}

    If the user enters a funny string like Robert'; DROP TABLE students; --, SQLite will see the following SQL, and drop your database table instead of updating a name as intended:

    UPDATE students SET name = 'Robert';
DROP TABLE students;
--' WHERE id = 1

    To avoid those problems, never embed raw values in your SQL queries. The only correct technique is to provide arguments to your SQL queries:

    // Good
let name = textField.text
try dbQueue.inDatabase { db in
    try db.execute(
        "UPDATE students SET name = ? WHERE id = ?",
        arguments: [name, id])
}

    See Executing Updates for more information on statement arguments.

    Error Handling

    GRDB can throw DatabaseError, PersistenceError, or crash your program with a fatal error.

    Considering that a local database is not some JSON loaded from a remote server, GRDB focuses on trusted databases. Dealing with untrusted databases requires extra care.

    DatabaseError

    DatabaseError are thrown on SQLite errors:

    do {
    try db.execute(
        "INSERT INTO pets (masterId, name) VALUES (?, ?)",
        arguments: [1, "Bobby"])
} catch let error as DatabaseError {
    // The SQLite error code: 19 (SQLITE_CONSTRAINT)
    error.resultCode

    // The extended error code: 787 (SQLITE_CONSTRAINT_FOREIGNKEY)
    error.extendedResultCode

    // The eventual SQLite message: FOREIGN KEY constraint failed
    error.message

    // The eventual erroneous SQL query
    // "INSERT INTO pets (masterId, name) VALUES (?, ?)"
    error.sql

    // Full error description:
    // "SQLite error 19 with statement `INSERT INTO pets (masterId, name)
    //  VALUES (?, ?)` arguments [1, "Bobby"]: FOREIGN KEY constraint failed""
    error.description
}

    SQLite uses codes to distinguish between various errors:

    do {
    try ...
} catch let error as DatabaseError where error.extendedResultCode == .SQLITE_CONSTRAINT_FOREIGNKEY {
    // foreign key constraint error
} catch let error as DatabaseError where error.resultCode == .SQLITE_CONSTRAINT {
    // any other constraint error
} catch let error as DatabaseError {
    // any other database error
}

    In the example above, error.extendedResultCode is a precise extended result code, and error.resultCode is a less precise primary result code. Extended result codes are refinements of primary result codes, as SQLITE_CONSTRAINT_FOREIGNKEY is to SQLITE_CONSTRAINT, for example. See SQLite result codes for more information.

    As a convenience, extended result codes match their primary result code in a switch statement:

    do {
    try ...
} catch let error as DatabaseError {
    switch error.extendedResultCode {
    case ResultCode.SQLITE_CONSTRAINT_FOREIGNKEY:
        // foreign key constraint error
    case ResultCode.SQLITE_CONSTRAINT:
        // any other constraint error
    default:
        // any other database error
    }
}

    :warning: Warning: SQLite has progressively introduced extended result codes accross its versions. For example, SQLITE_CONSTRAINT_FOREIGNKEY wasn’t introduced yet on iOS 8.1. The SQLite release notes are unfortunately not quite clear about that: write your handling of extended result codes with care.

    PersistenceError

    PersistenceError is thrown by the Persistable protocol, in a single case: when the update method could not find any row to update:

    do {
    try player.update(db)
} catch PersistenceError.recordNotFound {
    // There was nothing to update
}

    Fatal Errors

    Fatal errors notify that the program, or the database, has to be changed.

    They uncover programmer errors, false assumptions, and prevent misuses. Here are a few examples:

    • The code asks for a non-optional value, when the database contains NULL:

      // fatal error: could not convert NULL to String.
let name: String = row["name"]

      Solution: fix the contents of the database, use NOT NULL constraints, or load an optional:

      let name: String? = row["name"]

    • Conversion from database value to Swift type fails:

      // fatal error: could not convert "Mom’s birthday" to Date.
let date: Date = row["date"]

// fatal error: could not convert "" to URL.
let url: URL = row["url"]

      Solution: fix the contents of the database, or use DatabaseValue to handle all possible cases:

      let dbValue: DatabaseValue = row["date"]
if dbValue.isNull {
    // Handle NULL
} else if let date = Date.fromDatabaseValue(dbValue) {
    // Handle valid date
} else {
    // Handle invalid date
}

    • The database can’t guarantee that the code does what it says:

      // fatal error: table players has no unique index on column email
try Player.deleteOne(db, key: ["email": "arthur@example.com"])

      Solution: add a unique index to the players.email column, or use the deleteAll method to make it clear that you may delete more than one row:

      try Player.filter(Column("email") == "arthur@example.com").deleteAll(db)

    • Database connections are not reentrant:

      // fatal error: Database methods are not reentrant.
dbQueue.inDatabase { db in
    dbQueue.inDatabase { db in
        ...
    }
}

      Solution: avoid reentrancy, and instead pass a database connection along.

    How to Deal with Untrusted Inputs

    Let’s consider the code below:

    let sql = "SELECT ..."

// Some untrusted arguments for the query
let arguments: [String: Any] = ...
let rows = try Row.fetchCursor(db, sql, arguments: StatementArguments(arguments))

while let row = try rows.next() {
    // Some untrusted database value:
    let date: Date? = row[0]
}

    It has two opportunities to throw fatal errors:

    • Untrusted arguments: The dictionary may contain values that do not conform to the DatabaseValueConvertible protocol, or may miss keys required by the statement.
    • Untrusted database content: The row may contain a non-null value that can’t be turned into a date.

    In such a situation, you can still avoid fatal errors by exposing and handling each failure point, one level down in the GRDB API:

    // Untrusted arguments
if let arguments = StatementArguments(arguments) {
    let statement = try db.makeSelectStatement(sql)
    try statement.validate(arguments: arguments)
    statement.unsafeSetArguments(arguments)

    var cursor = try Row.fetchCursor(statement)
    while let row = try iterator.next() {
        // Untrusted database content
        let dbValue: DatabaseValue = row[0]
        if dbValue.isNull {
            // Handle NULL
        if let date = Date.fromDatabaseValue(dbValue) {
            // Handle valid date
        } else {
            // Handle invalid date
        }
    }
}

    See prepared statements and DatabaseValue for more information.

    Error Log

    SQLite can be configured to invoke a callback function containing an error code and a terse error message whenever anomalies occur.

    This global error callback must be configured early in the lifetime of your application:

    Database.logError = { (resultCode, message) in
    NSLog("%@", "SQLite error \(resultCode): \(message)")
}

    :warning: Warning: Database.logError must be set before any database connection is opened. This includes the connections that your application opens with GRDB, but also connections opened by other tools, such as third-party libraries. Setting it after a connection has been opened is an SQLite misuse, and has no effect.

    See The Error And Warning Log for more information.

    Unicode

    SQLite lets you store unicode strings in the database.

    However, SQLite does not provide any unicode-aware string transformations or comparisons.

    Unicode functions

    The UPPER and LOWER built-in SQLite functions are not unicode-aware:

    // "JéRôME"
try String.fetchOne(db, "SELECT UPPER('Jérôme')")

    GRDB extends SQLite with SQL functions that call the Swift built-in string functions capitalized, lowercased, uppercased, localizedCapitalized, localizedLowercased and localizedUppercased:

    // "JÉRÔME"
let uppercase = DatabaseFunction.uppercase
try String.fetchOne(db, "SELECT \(uppercased.name)('Jérôme')")

    Those unicode-aware string functions are also readily available in the query interface:

    Player.select(nameColumn.uppercased)

    String Comparison

    SQLite compares strings in many occasions: when you sort rows according to a string column, or when you use a comparison operator such as = and <=.

    The comparison result comes from a collating function, or collation. SQLite comes with three built-in collations that do not support Unicode: binary, nocase, and rtrim.

    GRDB comes with five extra collations that leverage unicode-aware comparisons based on the standard Swift String comparison functions and operators:

    • unicodeCompare (uses the built-in <= and == Swift operators)
    • caseInsensitiveCompare
    • localizedCaseInsensitiveCompare
    • localizedCompare
    • localizedStandardCompare

    A collation can be applied to a table column. All comparisons involving this column will then automatically trigger the comparison function:

    try db.create(table: "players") { t in
    // Guarantees case-insensitive email unicity
    t.column("email", .text).unique().collate(.nocase)

    // Sort names in a localized case insensitive way
    t.column("name", .text).collate(.localizedCaseInsensitiveCompare)
}

// Players are sorted in a localized case insensitive way:
let players = try Player.order(nameColumn).fetchAll(db)

    :warning: Warning: SQLite requires host applications to provide the definition of any collation other than binary, nocase and rtrim. When a database file has to be shared or migrated to another SQLite library of platform (such as the Android version of your application), make sure you provide a compatible collation.

    If you can’t or don’t want to define the comparison behavior of a column (see warning above), you can still use an explicit collation in SQL requests and in the query interface:

    let collation = DatabaseCollation.localizedCaseInsensitiveCompare
let players = try Player.fetchAll(db,
    "SELECT * FROM players ORDER BY name COLLATE \(collation.name))")
let players = try Player.order(nameColumn.collating(collation)).fetchAll(db)

    You can also define your own collations:

    let collation = DatabaseCollation("customCollation") { (lhs, rhs) -> NSComparisonResult in
    // return the comparison of lhs and rhs strings.
}
dbQueue.add(collation: collation) // Or dbPool.add(collation: ...)

    Memory Management

    Both SQLite and GRDB use non-essential memory that help them perform better.

    You can reclaim this memory with the releaseMemory method:

    // Release as much memory as possible.
dbQueue.releaseMemory()
dbPool.releaseMemory()

    This method blocks the current thread until all current database accesses are completed, and the memory collected.

    Memory Management on iOS

    The iOS operating system likes applications that do not consume much memory.

    Database queues and pools can call the releaseMemory method for you, when application receives memory warnings, and when application enters background: call the setupMemoryManagement method after creating the queue or pool instance:

    let dbQueue = try DatabaseQueue(...)
dbQueue.setupMemoryManagement(in: UIApplication.sharedApplication())

    Data Protection

    Data Protection lets you protect files so that they are encrypted and unavailable until the device is unlocked.

    Data protection can be enabled globally for all files created by an application.

    You can also explicitly protect a database, by configuring its enclosing directory. This will not only protect the database file, but also all temporary files created by SQLite (including the persistent .shm and .wal files created by database pools).

    For example, to explicitely use complete protection:

    // Paths
let fileManager = FileManager.default
let directoryURL = try fileManager
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("database", isDirectory: true)
let databaseURL = directoryURL.appendingPathComponent("db.sqlite")

// Create directory if needed
var isDirectory: ObjCBool = false
if !fileManager.fileExists(atPath: directoryURL.path, isDirectory: &isDirectory) {
    try fileManager.createDirectory(atPath: directoryURL.path, withIntermediateDirectories: false)
} else if !isDirectory.boolValue {
    throw NSError(domain: NSCocoaErrorDomain, code: NSFileWriteFileExistsError, userInfo: nil)
}

// Enable data protection
try fileManager.setAttributes([.protectionKey : FileProtectionType.complete], ofItemAtPath: directoryURL.path)

// Open database
let dbQueue = try DatabaseQueue(path: databaseURL.path)

    When a database is protected, an application that runs in the background on a locked device won’t be able to read or write from it. Instead, it will get DatabaseError with code SQLITE_IOERR (10) disk I/O error, or SQLITE_AUTH (23) not authorized.

    You can catch those errors and wait for UIApplicationDelegate.applicationProtectedDataDidBecomeAvailable(_:) or UIApplicationProtectedDataDidBecomeAvailable notification in order to retry the failed database operation.

    Concurrency

    Guarantees and Rules

    GRDB ships with three concurrency modes:

    • DatabaseQueue opens a single database connection, and serializes all database accesses.
    • DatabasePool manages a pool of several database connections, and allows concurrent reads and writes.
    • DatabaseSnapshot opens a single read-only database connection on an unchanging database content, and (currently) serializes all database accesses

    All foster application safety: regardless of the concurrency mode you choose, GRDB provides you with the same guarantees, as long as you follow three rules.

    • :bowtie: Guarantee 1: writes are always serialized. At every moment, there is no more than a single thread that is writing into the database.

      Database writes always happen in a unique serial dispatch queue, named the writer protected dispatch queue.

    • :bowtie: Guarantee 2: reads are always isolated. This means that they are guaranteed an immutable view of the last committed state of the database, and that you can perform subsequent fetches without fearing eventual concurrent writes to mess with your application logic:

      try dbPool.read { db in // or dbQueue.inDatabase { ... }
    // Guaranteed to be equal
    let count1 = try Player.fetchCount(db)
    let count2 = try Player.fetchCount(db)
}

      In database queues, reads happen in the same protected dispatch queue as writes: isolation is just a consequence of the serialization of database accesses

      Database pools and snapshots both use the snapshot isolation made possible by SQLite’s WAL mode (see Isolation In SQLite).

    • :bowtie: Guarantee 3: requests don’t fail, unless a database constraint violation, a programmer mistake, or a very low-level issue such as a disk error or an unreadable database file. GRDB grants correct use of SQLite, and particularly avoids locking errors and other SQLite misuses.

    Those guarantees hold as long as you follow three rules:

    • :point_up: Rule 1: Have a unique instance of DatabaseQueue or DatabasePool connected to any database file.

      This means that opening a new connection each time you access the database is probably a very bad idea. Do share a single connection instead.

      See, for example, DemoApps/GRDBDemoiOS/AppDatabase.swift for a sample code that properly sets up a single database queue that is available throughout the application.

      If there are several instances of database queues or pools that write in the same database, a multi-threaded application will eventually face database is locked errors. See Dealing with External Connections.

      // SAFE CONCURRENCY
func currentUser(_ db: Database) throws -> User? {
    return try User.fetchOne(db)
}
// dbQueue is a singleton defined somewhere in your app
let user = try dbQueue.inDatabase { db in // or dbPool.read { ... }
    try currentUser(db)
}

// UNSAFE CONCURRENCY
// This method fails when some other thread is currently writing into
// the database.
func currentUser() throws -> User? {
    let dbQueue = try DatabaseQueue(...)
    return try dbQueue.inDatabase { db in
        try User.fetchOne(db)
    }
}
let user = try currentUser()

    • :point_up: Rule 2: Group related statements within a single call to a DatabaseQueue or DatabasePool database access method (or use snapshots).

      Database access methods isolate your groups of related statements against eventual database updates performed by other threads, and guarantee a consistent view of the database. This isolation is only guaranteed inside the closure argument of those methods. Two consecutive calls do not guarantee isolation:

      // SAFE CONCURRENCY
try dbPool.read { db in  // or dbQueue.inDatabase { ... }
    // Guaranteed to be equal:
    let count1 = try Place.fetchCount(db)
    let count2 = try Place.fetchCount(db)
}

// UNSAFE CONCURRENCY
// Those two values may be different because some other thread may have
// modified the database between the two blocks:
let count1 = try dbPool.read { db in try Place.fetchCount(db) }
let count2 = try dbPool.read { db in try Place.fetchCount(db) }

      In the same vein, when you fetch values that depends on some database updates, group them:

      // SAFE CONCURRENCY
try dbPool.write { db in
    // The count is guaranteed to be non-zero
    try Place(...).insert(db)
    let count = try Place.fetchCount(db)
}

// UNSAFE CONCURRENCY
// The count may be zero because some other thread may have performed
// a deletion between the two blocks:
try dbPool.write { db in try Place(...).insert(db) }
let count = try dbPool.read { db in try Place.fetchCount(db) }

      On that last example, see Advanced DatabasePool if you look after extra performance.

    • :point_up: Rule 3: When you perform several modifications of the database that temporarily put the database in an inconsistent state, group those modifications within a transaction:

      // SAFE CONCURRENCY
try dbPool.writeInTransaction { db in  // or dbQueue.inTransaction { ... }
    try Credit(destinationAccout, amount).insert(db)
    try Debit(sourceAccount, amount).insert(db)
    return .commit
}

// UNSAFE CONCURRENCY
try dbPool.write { db in  // or dbQueue.inDatabase { ... }
    try Credit(destinationAccout, amount).insert(db)
    try Debit(sourceAccount, amount).insert(db)
}

      Without transaction, DatabasePool.read { ... } may see the first statement, but not the second, and access a database where the balance of accounts is not zero. A highly bug-prone situation.

      So do use transactions in order to guarantee database consistency accross your application threads: that’s what they are made for.

    Differences between Database Queues and Pools

    Despite the common guarantees and rules shared by database queues and pools, those two database accessors don’t have the same behavior.

    Database queues serialize all database accesses, reads, and writes. There is never more than one thread that uses the database. In the image on the left below, we see how three threads can see the database:

    Database Queue Database Pool
    Database Queue Scheduling Database Pool Scheduling

    Database pools serialize all writes, but allow concurrent reads and writes. On top of that, reads are guaranteed an immutable view of the database. This gives a very different picture (on the right).

    See, at the bottom of the image, how two threads can see different database states at the same time.

    Because of this behavior, one has to understand that all database pool reads may load stale data. Fortunately, the consequences of stale data can easily be alleviated by database observation, where GRDB shines.

    It is highly recommended, before you use database pools, that you grab general information about SQLite WAL mode, snapshot isolation, and GRDB database observation. They all fit very well together.

    Advanced DatabasePool

    Database pools are very concurrent, since all reads can run in parallel, and can even run during write operations. But writes are still serialized: at any given point in time, there is no more than a single thread that is writing into the database.

    When your application modifies the database, and then reads some value that depends on those modifications, you may want to avoid locking the writer queue longer than necessary:

    try dbPool.write { db in
    // Increment the number of players
    try Player(...).insert(db)

    // Read the number of players. The writer queue is still locked :-(
    let count = try Player.fetchCount(db)
}

    A wrong solution is to chain a write then a read, as below. Don’t do that, because another thread may modify the database in between, and make the read unreliable:

    // WRONG
try dbPool.write { db in
    // Increment the number of players
    try Player(...).insert(db)
}
try dbPool.read { db in
    // Read some random value :-(
    let count = try Player.fetchCount(db)
}

    The correct solution is the readFromCurrentState method, which must be called from within a write block:

    // CORRECT
try dbPool.write { db in
    // Increment the number of players
    try Player(...).insert(db)

    try dbPool.readFromCurrentState { db
        // Read the number of players. The writer queue has been unlocked :-)
        let count = try Player.fetchCount(db)
    }
}

    readFromCurrentState blocks until it can guarantee its closure argument an isolated access to the last committed state of the database. It then asynchronously executes the closure. If the isolated access can’t be established, readFromCurrentState throws an error, and the closure is not executed.

    The closure can run concurrently with eventual updates performed after readFromCurrentState: those updates won’t be visible from within the closure. In the example below, the number of players is guaranteed to be non-zero, even though it is fetched concurrently with the player deletion:

    try dbPool.write { db in
    // Increment the number of players
    try Player(...).insert(db)

    try dbPool.readFromCurrentState { db
        // Guaranteed to be non-zero
        let count = try Player.fetchCount(db)
    }

    try Player.deleteAll(db)
}

    Transaction Observers can also use readFromCurrentState in their databaseDidCommit method in order to process database changes without blocking other threads that want to write into the database.

    Database Snapshots

    A database snapshot sees an unchanging database content, as it existed at the moment it was created.

    Unchanging means that a snapshot never sees any database modifications during all its lifetime. And yet it doesn’t prevent database updates. This magic is made possible by SQLite’s WAL mode (see Isolation In SQLite).

    You create snapshots from a database pool:

    let snapshot = try dbPool.makeSnapshot()

    You can create as many snapshots as you need, regardless of the maximum number of readers in the pool. A snapshot database connection is closed when the snapshot gets deallocated.

    A snapshot can be used from any thread. Its read methods is synchronous, and blocks the current thread until your database statements are executed:

    // Read values:
try snapshot.read { db in
    let players = try Player.fetchAll(db)
    let playerCount = try Player.fetchCount(db)
}

// Extract a value from the database:
let playerCount = try snapshot.read { db in
    try Player.fetchCount(db)
}

    When you want to control the latest committed changes seen by a snapshot, create it from the pool’s writer protected dispatch queue:

    let snapshot1 = try dbPool.write { db -> DatabaseSnapshot in
    try Player.deleteAll()
    return dbPool.makeSnapshot()
}
// <- Other threads may modify the database here
let snapshot2 = try dbPool.makeSnapshot()

try snapshot1.read { db in
    // Guaranteed to be zero
    try Player.fetchCount(db)
}

try snapshot2.read { db in
    // Could be anything
    try Player.fetchCount(db)
}

    :point_up: Note: snapshots currently serialize all database accesses. In the future, snapshots may allow concurrent reads.

    DatabaseWriter and DatabaseReader Protocols

    Both DatabaseQueue and DatabasePool adopt the DatabaseReader and DatabaseWriter protocols. DatabaseSnapshot adopts DatabaseReader only.

    These protocols provide a unified API that lets you write safe concurrent code that targets all three concurrency modes.

    However, queues are not pools which are different from snapshots, and DatabaseReader and DatabaseWriter provide the smallest common guarantees. They require more discipline:

    • Pools are less forgiving than queues when one overlooks a transaction (see concurrency rule 3).
    • DatabaseWriter.readFromCurrentState is synchronous, or asynchronous, depending on whether it is run by a queue or a pool (see advanced DatabasePool). It thus requires higher libDispatch skills, and more complex synchronization code.

    DatabaseReader and DatabaseWriter are not a tool for applications that hesitate between DatabaseQueue and DatabasePool, and look for a common API. As seen above, the protocols actually make applications harder to write correctly. Instead, they target generic code that has both queues and pools in mind. The built-in AnyDatabaseReader and AnyDatabaseWriter type erasers serve the same purpose.

    DatabaseWriter and DatabaseReader fuel, for example:

    Unsafe Concurrency APIs

    Database queues, pools, snapshots, as well as their common protocols DatabaseReader and DatabaseWriter provide unsafe APIs. Unsafe APIs lift concurrency guarantees, and allow advanced yet unsafe patterns.

    • unsafeRead

      The unsafeRead method is synchronous, and blocks the current thread until your database statements are executed in a protected dispatch queue. GRDB does just the bare minimum to provide a database connection that can read.

      When used on a database pool, reads are no longer isolated:

      dbPool.unsafeRead { db in
    // Those two values may be different because some other thread
    // may have inserted or deleted a player between the two requests:
    let count1 = try Player.fetchCount(db)
    let count2 = try Player.fetchCount(db)
}

      When used on a datase queue, the closure argument is allowed to write in the database.

    • unsafeReentrantRead

      The unsafeReentrantRead behaves just as unsafeRead (see above), and allows reentrant calls:

      dbPool.read { db1 in
    // No "Database methods are not reentrant" fatal error:
    dbPool.unsafeReentrantRead { db2 in
        dbPool.unsafeReentrantRead { db3 in
            ...
        }
    }
}

      Reentrant database accesses make it very easy to break the second safety rule, which says: group related statements within a single call to a DatabaseQueue or DatabasePool database access method.. Using a reentrant method is pretty much likely the sign of a wrong application architecture that needs refactoring.

      Reentrant methods have been introduced in order to support RxGRDB, a set of reactive extensions to GRDB based on RxSwift that need precise scheduling.

    • unsafeReentrantWrite

      The unsafeReentrantWrite method is synchronous, and blocks the current thread until your database statements are executed in a protected dispatch queue. Writes are serialized: eventual concurrent database updates are postponed until the block has executed.

      Reentrant calls are allowed:

      dbQueue.inDatabase { db1 in
    // No "Database methods are not reentrant" fatal error:
    dbQueue.unsafeReentrantWrite { db2 in
        dbQueue.unsafeReentrantWrite { db3 in
            ...
        }
    }
}

      Reentrant database accesses make it very easy to break the second safety rule, which says: group related statements within a single call to a DatabaseQueue or DatabasePool database access method.. Using a reentrant method is pretty much likely the sign of a wrong application architecture that needs refactoring.

      Reentrant methods have been introduced in order to support RxGRDB, a set of reactive extensions to GRDB based on RxSwift that need precise scheduling.

    Dealing with External Connections

    The first rule of GRDB is:

    • Rule 1: Have a unique instance of DatabaseQueue or DatabasePool connected to any database file.

    This means that dealing with external connections is not a focus of GRDB. Guarantees of GRDB may or may not hold as soon as some external connection modifies a database.

    If you absolutely need multiple connections, then:

    Performance

    GRDB is a reasonably fast library, and can deliver quite efficient SQLite access. See Comparing the Performances of Swift SQLite libraries for an overview.

    You’ll find below general advice when you do look after performance:

    • Focus
    • Know your platform
    • Use transactions
    • Don’t do useless work
    • Learn about SQL strengths and weaknesses
    • Avoid strings & dictionaries

    Performance tip: focus

    You don’t know which part of your program needs improvement until you have run a benchmarking tool.

    Don’t make any assumption, avoid optimizing code too early, and use Instruments.

    Performance tip: know your platform

    If your application processes a huge JSON file and inserts thousands of rows in the database right from the main thread, it will quite likely become unresponsive, and provide a sub-quality user experience.

    If not done yet, read the Concurrency Programming Guide and learn how to perform heavy computations without blocking your application.

    Most GRBD APIs are synchronous. Spawning them into parallel queues is as easy as:

    DispatchQueue.global().async { 
    dbQueue.inDatabase { db in
        // Perform database work
    }
    DispatchQueue.main.async { 
        // update your user interface
    }
}

    Performance tip: use transactions

    Performing multiple updates to the database is much faster when executed inside a transaction. This is because a transaction allows SQLite to postpone writing changes to disk until the final commit:

    // Inefficient
try dbQueue.inDatabase { db in
    for player in players {
        try player.insert(db)
    }
}

// Efficient
try dbQueue.inTransaction { db in
    for player in players {
        try player.insert(db)
    }
    return .Commit
}

    Performance tip: don’t do useless work

    Obviously, no code is faster than any code.

    Don’t fetch columns you don’t use

    // SELECT * FROM players
try Player.fetchAll(db)

// SELECT id, name FROM players
try Player.select(idColumn, nameColumn).fetchAll(db)

    If your Player type can’t be built without other columns (it has non-optional properties for other columns), do define and use a different type.

    Don’t fetch rows you don’t use

    Use fetchOne when you need a single value, and otherwise limit your queries at the database level:

    // Wrong way: this code may discard hundreds of useless database rows
let players = try Player.order(scoreColumn.desc).fetchAll(db)
let hallOfFame = players.prefix(5)

// Better way
let hallOfFame = try Player.order(scoreColumn.desc).limit(5).fetchAll(db)

    Don’t copy values unless necessary

    Particularly: the Array returned by the fetchAll method, and the cursor returned by fetchCursor aren’t the same:

    fetchAll copies all values from the database into memory, when fetchCursor iterates database results as they are generated by SQLite, taking profit from SQLite efficiency.

    You should only load arrays if you need to keep them for later use (such as iterating their contents in the main thread). Otherwise, use fetchCursor.

    See fetching methods for more information about fetchAll and fetchCursor. See also the Row.dataNoCopy method.

    Don’t update rows unless necessary

    An UPDATE statement is costly: SQLite has to look for the updated row, update values, and write changes to disk.

    When the overwritten values are the same as the existing ones, it’s thus better to avoid performing the UPDATE statement:.

    if player.hasDatabaseChanges {
    try player.update(db)
}

    See changes tracking for more information.

    Performance tip: learn about SQL strengths and weaknesses

    Consider a simple use case: your store application has to display a list of authors with the number of available books:

    • J. M. Coetzee (6)
    • Herman Melville (1)
    • Alice Munro (3)
    • Kim Stanley Robinson (7)
    • Oliver Sacks (4)

    The following code is inefficient. It is an example of the N+1 problem, because it performs one query to load the authors, and then N queries, as many as there are authors. This turns very inefficient as the number of authors grows:

    // SELECT * FROM authors
let authors = try Author.fetchAll(db)
for author in authors {
    // SELECT COUNT(*) FROM books WHERE authorId = ...
    author.bookCount = try Book.filter(authorIdColumn == author.id).fetchCount(db)
}

    Instead, perform a single query:

    let sql = """
    SELECT authors.*, COUNT(books.id) AS bookCount
    FROM authors
    LEFT JOIN books ON books.authorId = authors.id
    GROUP BY authors.id
    """
let authors = try Author.fetchAll(db, sql)

    In the example above, consider extending your Author with an extra bookCount property, or define and use a different type.

    Generally, define indexes on your database tables, and use SQLite’s efficient query planning:

    Performance tip: avoid strings & dictionaries

    The String and Dictionary Swift types are better avoided when you look for the best performance.

    Now GRDB records, for your convenience, do use strings and dictionaries:

    class Player : Record {
    var id: Int64?
    var name: String
    var email: String

    required init(_ row: Row) {
        id = row["id"]       // String
        name = row["name"]   // String
        email = row["email"] // String
        super.init()
    }

    override func encode(to container: inout PersistenceContainer) {
        container["id"] = id              // String
        container["name"] = name          // String
        container["email"] = email        // String
    }
}

    When convenience hurts performance, you can still use records, but you have better avoiding their string and dictionary-based methods.

    For example, when fetching values, prefer loading columns by index:

    // Strings & dictionaries
let players = try Player.fetchAll(db)

// Column indexes
// SELECT id, name, email FROM players
let request = Player.select(idColumn, nameColumn, emailColumn)
let rows = try Row.fetchCursor(db, request)
while let row = try rows.next() {
    let id: Int64 = row[0]
    let name: String = row[1]
    let email: String = row[2]
    let player = Player(id: id, name: name, email: email)
    ...
}

    When inserting values, use reusable prepared statements, and set statements values with an array:

    // Strings & dictionaries
for player in players {
    try player.insert(db)
}

// Prepared statement
let insertStatement = db.prepareStatement("INSERT INTO players (name, email) VALUES (?, ?)")
for player in players {
    // Only use the unsafe arguments setter if you are sure that you provide
    // all statement arguments. A mistake can store unexpected values in
    // the database.
    insertStatement.unsafeSetArguments([player.name, player.email])
    try insertStatement.execute()
}

    FAQ

    How do I create a database in my application?

    This question assumes that your application has to create a new database from scratch. If your app has to open an existing database that is embedded inside your application as a resource, see How do I open a database stored as a resource of my application? instead.

    The database has to be stored in a valid place where it can be created and modified. For example, in the Application Support directory:

    let databaseURL = try FileManager.default
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("db.sqlite")
let dbQueue = try DatabaseQueue(path: databaseURL.path)

    How do I open a database stored as a resource of my application?

    If your application does not need to modify the database, open a read-only connection to your resource:

    var configuration = Configuration()
configuration.readonly = true
let dbPath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
let dbQueue = try DatabaseQueue(path: dbPath, configuration: configuration)

    If the application should modify the database, you need to copy it to a place where it can be modified. For example, in the Application Support directory. Only then, open a connection:

    let fileManager = FileManager.default
let dbPath = try fileManager
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("db.sqlite")
    .path
if !fileManager.fileExists(atPath: dbPath) {
    let dbResourcePath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
    try fileManager.copyItem(atPath: dbResourcePath, toPath: dbPath)
}
let dbQueue = try DatabaseQueue(path: dbPath)

    How do I close a database connection?

    Database connections are managed by database queues and pools. A connection is closed when its database queue or pool is deallocated, and all usages of this connection are completed.

    Database accesses that run in background threads postpone the closing of connections.

    How do I print a request as SQL?

    When you want to debug a request that does not deliver the expected results, you may want to print the SQL that is actually executed.

    Use the asSQLRequest method:

    try dbQueue.inDatabase { db in
    let request = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")

    let sqlRequest = try request.asSQLRequest(db)
    print(sqlRequest.sql)
    // Prints SELECT * FROM wines WHERE origin = ? ORDER BY price
    print(sqlRequest.arguments)
    // Prints ["Burgundy"]
}

    Another option is to setup a tracing function that will print out all SQL requests executed by your application. You provide the trace function when you connect to the database:

    var config = Configuration()
config.trace = { print("SQL: \($0)") } // Prints all SQL statements
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)

try dbQueue.inDatabase { db in
    let wines = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")
        .fetchAll(db)
    // Prints SELECT * FROM wines WHERE origin = 'Burgundy' ORDER BY price
}

    Generic parameter ‘T’ could not be inferred

    You may get this error when using DatabaseQueue.inDatabase, DatabasePool.read, or DatabasePool.write:

    // Generic parameter 'T' could not be inferred
let x = try dbQueue.inDatabase { db in
    let result = try String.fetchOne(db, ...)
    return result
}

    This is a Swift compiler issue (see SR-1570).

    The general workaround is to explicitly declare the type of the closure result:

    // General Workaround
let string = try dbQueue.inDatabase { db -> String? in
    let result = try String.fetchOne(db, ...)
    return result
}

    You can also, when possible, write a single-line closure:

    // Single-line closure workaround:
let string = try dbQueue.inDatabase { db in
    try String.fetchOne(db, ...)
}

    SQLite error 10 disk I/O error, SQLite error 23 not authorized

    Those errors may be the sign that SQLite can’t access the database due to data protection.

    When your application should be able to run in the background on a locked device, it has to catch this error, and, for example, wait for UIApplicationDelegate.applicationProtectedDataDidBecomeAvailable(_:) or UIApplicationProtectedDataDidBecomeAvailable notification and retry the failed database operation.

    This error can also be prevented altogether by using a more relaxed file protection.

    What Are Experimental Features?

    Since GRDB 1.0, all backwards compatibility guarantees of semantic versioning apply: no breaking change will happen until the next major version of the library.

    There is an exception, though: experimental features, marked with the **:fire: EXPERIMENTAL** badge. Those are advanced features that are too young, or lack user feedback. They are not stabilized yet.

    Those experimental features are not protected by semantic versioning, and may break between two minor releases of the library. To help them becoming stable, your feedback is greatly appreciated.

    Sample Code

    Thanks