Feature Launch: Databricks Reverse ETL source

If you’re using Databricks, you can now easily sync data from your data lakehouse to your entire stack with our DataBricks Reverse ETL (rETL) source. This new destination is a big unlock for teams building models or audiences in Databricks who want to push that data to marketing and product tools.

This new integration supports Databricks Unity Catalog and works with RudderStack’s visual data mapper and mirror mode features.

Top use cases for the Databricks Reverse ETL source

• Easily push AI/ML outputs to marketing tools to power better customer experiences
• Quickly respond to marketing requests for new data points
• Enrich lead and user records with comprehensive data
• Efficiently update millions of customer records from your warehouse

Key integration features

• Models: Utilize the power of custom SQL queries to build your models. Run these queries on your lakehouse through RudderStack and dispatch the results to any downstream business tool.
• Audiences: Our audiences feature enables non-technical users to build basic audiences with a robust user interface. This feature enables data teams to set up self-serve workflows for business teams.
• Visual Data Mapper (VDM): Use an intuitive UI to map your Databricks column names to fields in downstream SaaS tools.
• Mirror Mode: Mirror Mode ensures your data sent to downstream tools remains an exact replica of your source data in Databricks. It performs the insertion, updating, and deletion of records while synchronizing data to Databricks, ensuring your models stay updated.
• Unity Catalog Support: RudderStack supports Databricks Unity Catalog, meaning no changes to your existing modeling or workflows. Simply connect Databricks as a source and start sending data.

Get started

You can start sending data from Databricks to any of RudderStack’s 200+ destination integrations in a few simple steps. Log in to your RudderStack account, create a new source, select “Databricks,” and enter your Databricks credentials.

Next, add a destination, select the Databricks table you want to sync, configure the sync settings and schedule, and data will begin flowing from Databricks to the destination. Check out the Databricks Source documentation for more details.