Databricks Connector

Use Databricks as a source, destination, dbt Core warehouse, SQL task datasource, or activation source through Unity Catalog and Databricks SQL.

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Evaluating against Fivetran? See how Supaflow handles Databricks pricing, connector quality, and Snowflake deployment side-by-side.

Supaflow vs Fivetran

Why Supaflow

All connectors included

Every connector is available on every plan. Pricing does not increase with connector count.

Pay for compute, not rows

Credit-based pricing. Usage scales with your pipelines, not with row counts.

One platform

Ingestion, dbt Core transformation, reverse ETL, and orchestration in a single workspace.

Capabilities

Databricks as a Source and Destination

Replicate accessible Unity Catalog tables and views into another platform, or load data from any supported Supaflow source into Databricks tables.

OAuth and Token Authentication

Use OAuth machine-to-machine credentials for production service principals or a Databricks personal access token for testing.

Full Refresh and Incremental Reads

Read complete objects or use a reliable date or timestamp column for cursor-based incremental sync. Native Delta Change Data Feed is not used.

Warehouse-Native Workflows

Use the same Databricks datasource for dbt Core transformation projects, SQL Script tasks, and activation pipelines.

Supported Objects

Source Objects

Unity Catalog tables

Accessible tables across the catalogs and schemas visible to the configured identity.

Unity Catalog views

Accessible views whose columns and data can be read through the selected SQL warehouse.

Destination Objects

Unity Catalog tables

Pipeline output loaded into target catalogs and schemas with configurable load and schema-evolution behavior.

How It Works

Prepare the SQL warehouse

Choose a Databricks SQL warehouse and copy its Server Hostname and HTTP Path. Grant the connector identity CAN USE on the warehouse.

Configure authentication

Create OAuth machine-to-machine credentials for a Databricks service principal, or use a personal access token for testing.

Grant Unity Catalog access

Grant read access for source pipelines or table-creation and update access for destination pipelines. Destinations also need read and write access to an existing Unity Catalog volume.

Test and save

Enter the warehouse, catalog, schema, authentication, and destination-volume settings in Supaflow, then click Test & Save.

Use Cases

Load operational data into Databricks

Bring SaaS, database, file, and warehouse data into Unity Catalog tables for analytics and machine learning workflows.

Replicate Databricks data elsewhere

Move selected Databricks tables and views to another warehouse, database, or data lake.

Run dbt Core on Databricks

Create a Supaflow transformation project that builds dbt models against a Databricks target schema.

Activate Databricks data

Use curated Databricks tables as the source for activation pipelines that update supported business applications.

Frequently Asked Questions

Which authentication method should I use?

Use OAuth machine-to-machine authentication with a Databricks service principal for production. Personal access tokens are available for testing, but Databricks recommends OAuth where possible.

Does the source use Delta Change Data Feed?

No. The source supports full refresh and cursor-based incremental sync. It does not read Delta Change Data Feed and does not automatically detect hard deletes.

Why does the destination need a Unity Catalog volume?

The destination uses an existing Unity Catalog volume for temporary load files. The connector identity needs read and write access to that volume.

Can I use Databricks for dbt Core and SQL tasks?

Yes. A Databricks datasource can be selected by Supaflow dbt Core transformation projects and SQL Script tasks.