The Hub’s Database#

JupyterHub uses a database to store information about users, services, and other data needed for operating the Hub.

Default SQLite database#

The default database for JupyterHub is a SQLite database. We have chosen SQLite as JupyterHub’s default for its lightweight simplicity in certain uses such as testing, small deployments and workshops.

For production systems, SQLite has some disadvantages when used with JupyterHub:

  • upgrade-db may not work, and you may need to start with a fresh database

  • downgrade-db will not work if you want to rollback to an earlier version, so backup the jupyterhub.sqlite file before upgrading

The sqlite documentation provides a helpful page about when to use SQLite and where traditional RDBMS may be a better choice.

Using an RDBMS (PostgreSQL, MySQL)#

When running a long term deployment or a production system, we recommend using a traditional RDBMS database, such as PostgreSQL or MySQL, that supports the SQL ALTER TABLE statement.

Notes and Tips#


The SQLite database should not be used on NFS. SQLite uses reader/writer locks to control access to the database. This locking mechanism might not work correctly if the database file is kept on an NFS filesystem. This is because fcntl() file locking is broken on many NFS implementations. Therefore, you should avoid putting SQLite database files on NFS since it will not handle well multiple processes which might try to access the file at the same time.


We recommend using PostgreSQL for production if you are unsure whether to use MySQL or PostgreSQL or if you do not have a strong preference. There is additional configuration required for MySQL that is not needed for PostgreSQL.

MySQL / MariaDB#

  • You should use the pymysql sqlalchemy provider (the other one, MySQLdb, isn’t available for py3).

  • You also need to set pool_recycle to some value (typically 60 - 300) which depends on your MySQL setup. This is necessary since MySQL kills connections serverside if they’ve been idle for a while, and the connection from the hub will be idle for longer than most connections. This behavior will lead to frustrating ‘the connection has gone away’ errors from sqlalchemy if pool_recycle is not set.

  • If you use utf8mb4 collation with MySQL earlier than 5.7.7 or MariaDB earlier than 10.2.1 you may get an 1709, Index column size too large error. To fix this you need to set innodb_large_prefix to enabled and innodb_file_format to Barracuda to allow for the index sizes jupyterhub uses. row_format will be set to DYNAMIC as long as those options are set correctly. Later versions of MariaDB and MySQL should set these values by default, as well as have a default DYNAMIC row_format and pose no trouble to users.