Data Types

Turso uses the same dynamic type system as SQLite, where values have types but columns do not enforce a single type (unless using STRICT tables). Every value stored in Turso belongs to one of five storage classes. Turso extends this system with custom types, composite types, and native array types for STRICT tables.

Storage Classes

SELECT typeof(NULL);       -- 'null'
SELECT typeof(42);         -- 'integer'
SELECT typeof(3.14);       -- 'real'
SELECT typeof('hello');    -- 'text'
SELECT typeof(x'CAFE');    -- 'blob'

Type Affinity

When a column is declared with a type name, Turso assigns a type affinity to that column. Type affinity is a recommendation for how to store values, not a strict constraint (unless using STRICT tables). Turso uses the same affinity rules as SQLite.

Affinity Determination Rules

The type affinity of a column is determined by the declared type name, using these rules applied in order:

-- Type affinity is a suggestion, not a constraint
CREATE TABLE flexible (
    id INTEGER,
    name TEXT,
    data BLOB
);

-- This works - TEXT value in an INTEGER column
INSERT INTO flexible VALUES ('not a number', 42, 'text in blob');
SELECT typeof(id), typeof(name), typeof(data) FROM flexible;
-- 'text', 'integer', 'text'

Type Conversions

When a value is inserted into a column, Turso attempts to convert the value to the column's affinity:

• INTEGER affinity: If the value is TEXT or REAL that looks like an integer, Turso converts the value to INTEGER
• REAL affinity: If the value is TEXT that looks like a number, Turso converts to REAL. If the value is an integer, Turso converts to REAL
• NUMERIC affinity: Turso tries INTEGER first, then REAL, then keeps as TEXT
• TEXT affinity: Integer and REAL values are converted to their text representation
• BLOB affinity: No conversion is attempted

STRICT Tables

STRICT tables enforce type checking at the storage layer. Every value inserted into a STRICT table must match the declared column type or be convertible to the column type.

CREATE TABLE users (
    id INTEGER PRIMARY KEY,
    name TEXT NOT NULL,
    age INTEGER,
    score REAL
) STRICT;

-- This works - values match declared types
INSERT INTO users VALUES (1, 'Alice', 30, 95.5);

-- This fails - 'thirty' cannot be converted to INTEGER
INSERT INTO users VALUES (2, 'Bob', 'thirty', 80.0);
-- Error: cannot store TEXT value in INTEGER column

Allowed Types in STRICT Tables

STRICT tables only allow these base type names:

Custom Types

Custom types let you define how values are encoded before storage and decoded when read, enforce domain constraints at the storage layer, attach operators, and provide defaults. Custom types are declared with the CREATE TYPE statement.

-- A type that stores monetary values as cents
CREATE TYPE cents BASE integer
    ENCODE value * 100
    DECODE value / 100;

CREATE TABLE prices (
    id INTEGER PRIMARY KEY,
    amount cents
) STRICT;

INSERT INTO prices VALUES (1, 42);
SELECT amount FROM prices;
-- 42  (stored on disk as 4200)

Built-in Custom Types

Turso provides several built-in custom types available in STRICT tables:

CREATE TABLE events (
    id uuid PRIMARY KEY,
    name varchar(100),
    event_date date,
    is_active boolean DEFAULT 1,
    metadata json
) STRICT;

INSERT INTO events VALUES (
    uuid4(),
    'Product Launch',
    '2025-03-15',
    1,
    '{"venue": "online"}'
);

For the full custom types reference including ENCODE/DECODE, operators, parametric types, and validation, see CREATE TYPE.

Composite Types: STRUCT and UNION

Turso also supports composite types: STRUCT (named product type) and UNION (discriminated union). These let you store structured data in a single column and access it with dot notation.

-- STRUCT: group related fields, access with col.field
CREATE TYPE point AS STRUCT(x INT, y INT);
CREATE TABLE locations(id INT PRIMARY KEY, pos point) STRICT;
INSERT INTO locations VALUES (1, struct_pack(10, 20));
SELECT pos.x, pos.y FROM locations WHERE pos.x > 5;
-- 10|20

-- UNION: tagged variants, access with col.variant
CREATE TYPE platform_id AS UNION(telegram INT, slack TEXT);
CREATE TABLE contacts(id INT PRIMARY KEY, platform platform_id) STRICT;
INSERT INTO contacts VALUES (1, union_value('telegram', 12345));
INSERT INTO contacts VALUES (2, union_value('slack', 'U0ABC'));
SELECT id, platform.telegram, platform.slack FROM contacts ORDER BY id;
-- 1|12345|
-- 2||U0ABC

For the full composite types reference, see CREATE TYPE — Composite Types.

Array Types

Array columns store ordered collections of values. Declare them by appending [] to any base type name:

CREATE TABLE sensors (
    id INTEGER PRIMARY KEY,
    readings REAL[],
    labels TEXT[],
    flags INTEGER[]
) STRICT;

Multi-dimensional arrays are supported with multiple bracket pairs:

CREATE TABLE matrices (
    id INTEGER PRIMARY KEY,
    data INTEGER[][]
) STRICT;

Arrays can be inserted using the ARRAY[...] constructor or as JSON text:

INSERT INTO sensors VALUES (1, ARRAY[1.5, 2.5, 3.5], '["a","b"]', '[0, 1, 1]');

Arrays are displayed as JSON arrays on output. Element types are validated against the declared base type — for example, an INTEGER[] column rejects non-numeric text elements.

For the full set of array functions, operators, and subscript syntax, see Array Functions.

Inspecting Types

List all available types (built-in and custom):

PRAGMA list_types;

All types are also available through the sqlite_turso_types virtual table:

SELECT name, sql FROM sqlite_turso_types;

Comparison and Sorting

Turso uses the same comparison rules as SQLite. Values of different storage classes are ordered as:

NULL < INTEGER/REAL < TEXT < BLOB

• NULL values are considered less than any other value
• INTEGER and REAL values are compared numerically
• TEXT values are compared using the column's collation sequence (default: BINARY)
• BLOB values are compared using memcmp()

SELECT 1 < 2;          -- 1 (true)
SELECT 'abc' < 'abd';  -- 1 (true)
SELECT 1 < '2';        -- 1 (true, numeric < text)
SELECT NULL < 1;        -- NULL (any comparison with NULL yields NULL)
SELECT NULL IS NULL;    -- 1 (use IS to test for NULL)

See Also

• CREATE TABLE for column definitions and constraints
• CREATE TYPE for custom type definitions
• Array Functions for array construction, manipulation, and operators
• Expressions for CAST expressions and type conversions
• Compatibility for differences from SQLite