Databases
The default database engine of Woodpecker is an embedded SQLite database which requires zero installation or configuration. But you can replace it with a MySQL/MariaDB or Postgres database.
Configure SQLiteโ
By default Woodpecker uses a SQLite database stored under /var/lib/woodpecker/
. If using containers, you can mount a data volume to persist the SQLite database.
services:
woodpecker-server:
[...]
+ volumes:
+ - woodpecker-server-data:/var/lib/woodpecker/
Configure MySQL/MariaDBโ
The below example demonstrates MySQL database configuration. See the official driver documentation for configuration options and examples.
The minimum version of MySQL/MariaDB required is determined by the go-sql-driver/mysql
- see it's README for more information.
WOODPECKER_DATABASE_DRIVER=mysql
WOODPECKER_DATABASE_DATASOURCE=root:password@tcp(1.2.3.4:3306)/woodpecker?parseTime=true
Configure Postgresโ
The below example demonstrates Postgres database configuration. See the official driver documentation for configuration options and examples. Please use Postgres versions equal or higher than 11.
WOODPECKER_DATABASE_DRIVER=postgres
WOODPECKER_DATABASE_DATASOURCE=postgres://root:password@1.2.3.4:5432/postgres?sslmode=disable
Database Creationโ
Woodpecker does not create your database automatically. If you are using the MySQL or Postgres driver you will need to manually create your database using CREATE DATABASE
.
Database Migrationโ
Woodpecker automatically handles database migration, including the initial creation of tables and indexes. New versions of Woodpecker will automatically upgrade the database unless otherwise specified in the release notes.
Database Backupsโ
Woodpecker does not perform database backups. This should be handled by separate third party tools provided by your database vendor of choice.
Database Archivingโ
Woodpecker does not perform data archival; it considered out-of-scope for the project. Woodpecker is rather conservative with the amount of data it stores, however, you should expect the database logs to grow the size of your database considerably.