Salesforce Marketing Cloud connector

Beta

This feature is in Beta. Workspace admins can control access to this feature from the Previews page. See Manage Databricks previews.

The managed Salesforce Marketing Cloud connector in Lakeflow Connect allows you to ingest data from Salesforce Marketing Cloud into 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	N/A

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
Databricks user persona	The workflow depends on your Databricks user persona: Single-user: An admin user creates a Unity Catalog connection and an ingestion pipeline. Multi-user: An admin user creates a connection for non-admin users to create pipelines with.
Authentication method	Server-to-Server OAuth requires an API Integration Package in Salesforce Marketing Cloud. See Configure OAuth for Salesforce Marketing Cloud ingestion into 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:

1. Configure Salesforce Marketing Cloud to enable authentication from Databricks. See Configure OAuth for Salesforce Marketing Cloud ingestion into Databricks.
2. 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.