You may choose different catalog databases for your DuckLake. The choice depends on several factors, including whether you need to use multiple clients, which database systems are available in your organization, etc.

On the technical side, consider the following:

• If you would like to perform local data warehousing with a single client, use DuckDB as the catalog database.
• If you would like to perform local data warehousing using multiple local clients, use SQLite as the catalog database.
• If you would like to operate a multi-user lakehouse with potentially remote clients, choose a transactional client-server database system as the catalog database: MySQL or PostgreSQL.

DuckDB

DuckDB can, of course, natively connect to DuckDB database files. So, to get started, you only need to install the ducklake extension and attach to your DuckLake:

INSTALL ducklake;

ATTACH 'ducklake:metadata.ducklake' AS my_ducklake;
USE my_ducklake;

Note that if you are using DuckDB as your catalog database, you're limited to a single client.

PostgreSQL

DuckDB can interact with a PostgreSQL database using the postgres extension. Install the ducklake and the postgres extension, and attach to your DuckLake as follows:

INSTALL ducklake;
INSTALL postgres;

-- Make sure that the database `ducklake_catalog` exists in PostgreSQL.
ATTACH 'ducklake:postgres:dbname=ducklake_catalog host=localhost' AS my_ducklake
    (DATA_PATH 'data_files/');
USE my_ducklake;

For details on how to configure the connection, see the postgres extension's documentation.

The ducklake and postgresql extensions require PostgreSQL 12 or newer.

SQLite

DuckDB can read and write a SQLite database file using the sqlite extension. Install the ducklake and the sqlite extension, and attach to your DuckLake as follows:

INSTALL ducklake;
INSTALL sqlite;

ATTACH 'ducklake:sqlite:metadata.sqlite' AS my_ducklake
    (DATA_PATH 'data_files/');
USE my_ducklake;

While SQLite doesn't allow concurrent reads and writes, its default mode is to ATTACH and DETACH for every query, together with providing a “retry time-out” for queries when a write-lock is encountered. This allows a reasonable amount of multi-processing support (effectively hiding the single-writer model).

MySQL

DuckDB can interact with a MySQL database using the mysql extension. Install the ducklake and the mysql extension, and attach to your DuckLake as follows:

INSTALL ducklake;
INSTALL mysql;

-- Make sure that the database `ducklake_catalog` exists in MySQL
ATTACH 'ducklake:mysql:db=ducklake_catalog host=localhost' AS my_ducklake
    (DATA_PATH 'data_files/');
USE my_ducklake;

For details on how to configure the connection, see the mysql extension's documentation.

Using the ducklake and mysql extensions require MySQL 8 or newer.