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SQLite Extension

The SQLite extension allows DuckDB to directly read and write data from a SQLite database file. The data can be queried directly from the underlying SQLite tables. Data can be loaded from SQLite tables into DuckDB tables, or vice versa.

Installing and Loading

To install the sqlite extension, run:

INSTALL sqlite;

The extension is loaded automatically upon first use. If you prefer to load it manually, run:

LOAD sqlite;

Usage

To make a SQLite file accessible to DuckDB, use the ATTACH statement, which supports read & write.

For example with the sakila.db file:

ATTACH 'sakila.db' (TYPE SQLITE);
USE sakila;

The tables in the file can be read as if they were normal DuckDB tables, but the underlying data is read directly from the SQLite tables in the file at query time.

SHOW TABLES;
┌────────────────────────┐
│          name          │
├────────────────────────┤
│ actor                  │
│ address                │
│ category               │
│ city                   │
│ country                │
│ customer               │
│ customer_list          │
│ film                   │
│ film_actor             │
│ film_category          │
│ film_list              │
│ film_text              │
│ inventory              │
│ language               │
│ payment                │
│ rental                 │
│ sales_by_film_category │
│ sales_by_store         │
│ staff                  │
│ staff_list             │
│ store                  │
└────────────────────────┘

You can query the tables using SQL, e.g., using the example queries from sakila-examples.sql:

SELECT
    cat.name AS category_name,
    sum(ifnull(pay.amount, 0)) AS revenue
FROM category cat
LEFT JOIN film_category flm_cat
       ON cat.category_id = flm_cat.category_id
LEFT JOIN film fil
       ON flm_cat.film_id = fil.film_id
LEFT JOIN inventory inv
       ON fil.film_id = inv.film_id
LEFT JOIN rental ren
       ON inv.inventory_id = ren.inventory_id
LEFT JOIN payment pay
       ON ren.rental_id = pay.rental_id
GROUP BY cat.name
ORDER BY revenue DESC
LIMIT 5;

Data Types

SQLite is a weakly typed database system. As such, when storing data in a SQLite table, types are not enforced. The following is valid SQL in SQLite:

CREATE TABLE numbers (i INTEGER);
INSERT INTO numbers VALUES ('hello');

DuckDB is a strongly typed database system, as such, it requires all columns to have defined types and the system rigorously checks data for correctness.

When querying SQLite, DuckDB must deduce a specific column type mapping. DuckDB follows SQLite’s type affinity rules with a few extensions.

  1. If the declared type contains the string INT then it is translated into the type BIGINT
  2. If the declared type of the column contains any of the strings CHAR, CLOB, or TEXT then it is translated into VARCHAR.
  3. If the declared type for a column contains the string BLOB or if no type is specified then it is translated into BLOB.
  4. If the declared type for a column contains any of the strings REAL, FLOA, DOUB, DEC or NUM then it is translated into DOUBLE.
  5. If the declared type is DATE, then it is translated into DATE.
  6. If the declared type contains the string TIME, then it is translated into TIMESTAMP.
  7. If none of the above apply, then it is translated into VARCHAR.

As DuckDB enforces the corresponding columns to contain only correctly typed values, we cannot load the string “hello” into a column of type BIGINT. As such, an error is thrown when reading from the “numbers” table above:

Error: Mismatch Type Error: Invalid type in column "i": column was declared as integer, found "hello" of type "text" instead.

This error can be avoided by setting the sqlite_all_varchar option:

SET GLOBAL sqlite_all_varchar = true;

When set, this option overrides the type conversion rules described above, and instead always converts the SQLite columns into a VARCHAR column. Note that this setting must be set before sqlite_attach is called.

Opening SQLite Databases Directly

SQLite databases can also be opened directly and can be used transparently instead of a DuckDB database file. In any client, when connecting, a path to a SQLite database file can be provided and the SQLite database will be opened instead.

For example, with the shell:

duckdb data/db/sakila.db 
SHOW tables;
┌────────────┐
│    name    │
│  varchar   │
├────────────┤
│ actor      │
│ address    │
│ category   │
│    ·       │
│ staff_list │
│ store      │
├────────────┤
│  21 rows   │
│ (5 shown)  │
└────────────┘

Writing Data to SQLite

In addition to reading data from SQLite, the extension also allows you to create new SQLite database files, create tables, ingest data into SQLite and make other modifications to SQLite database files using standard SQL queries.

This allows you to use DuckDB to, for example, export data that is stored in a SQLite database to Parquet, or read data from a Parquet file into SQLite.

Below is a brief example of how to create a new SQLite database and load data into it.

ATTACH 'new_sqlite_database.db' AS sqlite_db (TYPE SQLITE);
CREATE TABLE sqlite_db.tbl(id INTEGER, name VARCHAR);
INSERT INTO sqlite_db.tbl VALUES (42, 'DuckDB');

The resulting SQLite database can then be read into from SQLite.

sqlite3 new_sqlite_database.db 
SQLite version 3.39.5 2022-10-14 20:58:05
sqlite> SELECT * FROM tbl;
id  name  
--  ------
42  DuckDB

Many operations on SQLite tables are supported. All these operations directly modify the SQLite database, and the result of subsequent operations can then be read using SQLite.

Below is a list of supported operations.

CREATE TABLE

CREATE TABLE sqlite_db.tbl(id INTEGER, name VARCHAR);

INSERT INTO

INSERT INTO sqlite_db.tbl VALUES (42, 'DuckDB');

SELECT

SELECT * FROM sqlite_db.tbl;
┌───────┬─────────┐
│  id   │  name   │
│ int64 │ varchar │
├───────┼─────────┤
│    42 │ DuckDB  │
└───────┴─────────┘

COPY

COPY sqlite_db.tbl TO 'data.parquet';
COPY sqlite_db.tbl FROM 'data.parquet';

UPDATE

UPDATE sqlite_db.tbl SET name = 'Woohoo' WHERE id = 42;

DELETE

DELETE FROM sqlite_db.tbl WHERE id = 42;

ALTER TABLE

ALTER TABLE sqlite_db.tbl ADD COLUMN k INTEGER;

DROP TABLE

DROP TABLE sqlite_db.tbl;

CREATE VIEW

CREATE VIEW sqlite_db.v1 AS SELECT 42;

Transactions

CREATE TABLE sqlite_db.tmp(i INTEGER);
BEGIN;
INSERT INTO sqlite_db.tmp VALUES (42);
SELECT * FROM sqlite_db.tmp;
┌───────┐
│   i   │
│ int64 │
├───────┤
│    42 │
└───────┘
ROLLBACK;
SELECT * FROM sqlite_db.tmp;
┌────────┐
│   i    │
│ int64  │
├────────┤
│ 0 rows │
└────────┘

Deprecated The old sqlite_attach function is deprecated. It is recommended to switch over to the new ATTACH syntax.