Create MySQL Integration

To query a MySQL database from inside Workspace, the first step is creating an integration to connect to the database:
  • Create a new integration from the Integrations tab on the dashboard (link) or by clicking on
    in the sidebar when editing a workspace.
  • Select "MySQL".
  • Enter the credentials.
Create a MySQL integration
Workspace will access your database through a set of static IP addresses. You may need to whitelist these addresses in your database's firewall for queries to run successfully.
You can only connect to a database server that is available on the internet. You can not use Workspace to connect to a database server that is running on your computer (i.e. on localhost), unless you expose this server to the internet through tools like ngrok or Tailscale.

Use our sample database

If you want to experiment with this integration but don't have a MySQL database lying around, you can use our sample database containing data on employees (source).
You can select the sample integration in the dropdown when you create a SQL cell. Alternatively, you can open a workspace with a sample query and visualization of the data already prepared.
Example of connecting a sample database integration

Query the database

After creating the integration, you can query the database with a SQL cell. When you're editing a workspace:
  • Click "Add SQL cell" at the bottom of the notebook (or on "Add SQL cell" when hovering on the area in between two cells).
  • Select the integration that accesses the database you want to query.
  • (Optional) Update the variable name of the data frame that will hold the result of your SQL query by updating the field behind "Available as". If you don't set this, the query result will be available as a data frame called df.
  • Write the SQL query.
  • Click "Run" in the cell menu (or use the shortcuts).
Example of a running a query against the employees-test integration that connects to the employees database introduced in the previous section. The query result is available as employees_df.