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To connect to Databricks, first install databricks-dbapi with the optional SQLAlchemy dependencies:

pip install databricks-dbapi[sqlalchemy]

There are two ways to connect to Databricks: using a Hive connector or an ODBC connector. Both ways work similarly, but only ODBC can be used to connect to SQL endpoints.


To use the Hive connector you need the following information from your cluster:

  • Server hostname
  • Port
  • HTTP path

These can be found under "Configuration" -> "Advanced Options" -> "JDBC/ODBC".

You also need an access token from "Settings" -> "User Settings" -> "Access Tokens".

Once you have all this information, add a database of type "Databricks (Hive)" in Superset, and use the following SQLAlchemy URI:

databricks+pyhive://token:{access token}@{server hostname}:{port}/{database name}

You also need to add the following configuration to "Other" -> "Engine Parameters", with your HTTP path:

{"connect_args": {"http_path": "sql/protocolv1/o/****"}}


For ODBC you first need to install the ODBC drivers for your platform.

For a regular connection use this as the SQLAlchemy URI:

databricks+pyodbc://token:{access token}@{server hostname}:{port}/{database name}

And for the connection arguments:

{"connect_args": {"http_path": "sql/protocolv1/o/****", "driver_path": "/path/to/odbc/driver"}}

The driver path should be:

  • /Library/simba/spark/lib/libsparkodbc_sbu.dylib (Mac OS)
  • /opt/simba/spark/lib/64/ (Linux)

For a connection to a SQL endpoint you need to use the HTTP path from the endpoint:

{"connect_args": {"http_path": "/sql/1.0/endpoints/****", "driver_path": "/path/to/odbc/driver"}}