Databricks JDBC Driver Download

Download the Databricks JDBC driver, copy the JDBC URL into DbSchema, and start designing schemas with ER diagrams — free Community Edition.

About the Databricks JDBC driver

A JDBC driver is a Java .jar library that lets applications connect to Databricks. DbSchema uses JDBC to reverse engineer schemas, run SQL, and generate documentation. Driver files are usually published by the database vendor or an open-source project.

JDBC URL format

Host, port, database name, and SSL options are passed in a URL starting with jdbc:. Each Databricks driver uses its own syntax — see the connection details below.

The Databricks JDBC driver

Databricks is a unified data analytics platform built on Apache Spark, providing a lakehouse architecture that combines the flexibility of data lakes with the reliability of data warehouses. It supports Delta Lake, MLflow, and collaborative notebooks for data engineering and ML workflows.

The Databricks JDBC URL

We use the Spark JDBC driver to connect to Databricks SQL warehouses.

• Required File(s): SparkJDBC42.jar
• Java Driver Class: com.simba.spark.jdbc.Driver
• JDBC URL: jdbc:spark://HOST:PORT/default;transportMode=http;ssl=1;httpPath=...
• Website: Databricks

Download Databricks JDBC Driver

The driver archive is a zip file. Extract it and load the .jar files using DbSchema's Driver Manager.

Set Up the Databricks Connection

Every value you need sits on one page in the workspace, and one of them — the HTTP path — has no equivalent in any other JDBC connection.

1. Copy the JDBC URL from the Databricks workspace. You will find it in the SQL warehouse's Connection details tab, which lists the server hostname, the port and the HTTP path together.
2. Keep the HTTP path. httpPath identifies which warehouse or cluster the request goes to; host and port alone reach the workspace but not a compute resource. It is the parameter most often lost when a URL is retyped.
3. Authenticate with a personal access token. Generate one in your user settings, then set the user to the literal word token and paste the token as the password. That is what AuthMech=3;UID=token in the URL means. Databricks positions personal access tokens as suitable for testing and recommends stronger methods such as OAuth for production use.
4. Start the warehouse. A stopped SQL warehouse accepts the connection and then takes a while to answer while it starts, which can look like a hang. Start it in the workspace first, or allow a generous timeout on the first connection.
5. Paste the URL into DbSchema. In the Connection Dialog set Connection Mode to Edit the JDBC URL Manually and paste the string you copied. The user and the password are entered in the first tab, not in the URL.

Port 443 is used throughout, so there is rarely a firewall to change — outbound HTTPS is normally already allowed.

DbSchema and Databricks

DbSchema connects to Databricks SQL warehouses via the Spark JDBC driver and renders Delta Lake table schemas as interactive diagrams. Use the Schema Synchronization feature to compare table definitions across Databricks environments and generate the DDL diff.