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Important
This feature is in Beta. Workspace admins can control access to this feature from the Previews page. See Manage Azure Databricks previews.
The managed Salesforce Marketing Cloud connector in Lakeflow Connect allows you to ingest data from Salesforce Marketing Cloud into Azure Databricks.
Feature availability
| Feature | Availability |
|---|---|
| UI-based pipeline authoring |  Supported |
| API-based pipeline authoring | Supported |
| Declarative Automation Bundles | Supported |
| Incremental ingestion | Partially supported Most default tables support incremental ingestion. Batch-only tables are fully refreshed on each pipeline run. See Supported objects. |
| Unity Catalog governance | Supported |
| Lakeflow Jobs | Supported |
| SCD type 2 | Partially supported Supported for tables with a primary key. Not supported for tables without a primary key (uses __databricks_id). See Primary keys and history tracking. |
| Column selection and deselection | Supported |
| API-based row filtering |  Not supported |
| Automated schema evolution: New and deleted columns | Supported |
| Automated schema evolution: Data type changes | Not supported |
| Automated schema evolution: Column renames | Not supported |
| Automated schema evolution: New tables | Not supported |
Authentication methods
| Authentication method | Availability |
|---|---|
| OAuth M2M (Server-to-Server) | Supported |
| OAuth U2M | Not supported |
| Basic authentication (username/password) | Not supported |
| Basic authentication (API key) | Not supported |
What to know before you start
| Topic | Why it matters |
|---|---|
| Azure Databricks user persona | The workflow depends on your Azure Databricks user persona:
|
| Authentication method | Server-to-Server OAuth requires an API Integration Package in Salesforce Marketing Cloud. See Configure OAuth for Salesforce Marketing Cloud ingestion into Azure Databricks. |
| Source schemas | Each pipeline targets a single source schema type (default, dataextensions, and so on). You can combine multiple objects with different schemas in one pipeline. |
| Ingestion frequency | The pipeline schedule depends on your latency and cost requirements. |
| Common patterns | Depending on your ingestion needs, the pipeline might use configurations like history tracking and column selection. Supported configurations vary by connector. See Feature availability. |
Start ingesting from Salesforce Marketing Cloud
Admin:
- Configure Salesforce Marketing Cloud to enable authentication from Azure Databricks. See Configure OAuth for Salesforce Marketing Cloud ingestion into Azure Databricks.
- Use Catalog Explorer to create a connection so that non-admins can create pipelines. See Create a Salesforce Marketing Cloud connection.
Non-admin: Use any supported interface to create a pipeline from an existing connection. See Ingest data from Salesforce Marketing Cloud.