Meta Ads connector

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 Meta Ads connector in Lakeflow Connect allows you to ingest advertising data from Meta Ads into Azure Databricks.

Feature availability

Feature Availability
UI-based pipeline authoring Red X icon Not supported
API-based pipeline authoring Green check icon Supported
Declarative Automation Bundles Green check icon Supported
Incremental ingestion Green check icon Partially supported
Report tables support incremental ingestion. Resource tables are fully refreshed on each update.
Unity Catalog governance Green check icon Supported
Lakeflow Jobs Green check icon Supported
SCD type 2 Green check icon Partially supported
Supported for the ads, ad_sets, and campaigns tables using updated_time as the cursor column. Not supported for the other tables: ad_insights is an aggregated metric whose values Meta continuously refines within the attribution lookback window, ad_images is immutable in the source, and the remaining tables are fetched as full snapshots.
Column selection and deselection Green check icon Supported
You can select specific tables.
API-based row filtering Red X icon Not supported
Automated schema evolution: New and deleted columns Red X icon Not supported
Automated schema evolution: Data type changes Red X icon Not supported
Automated schema evolution: Column renames Red X icon Not supported
Automated schema evolution: New tables N/A
Maximum number of tables per pipeline 250

Authentication methods

Authentication method Availability
OAuth U2M Green check icon Supported
OAuth M2M Red X icon Not supported
OAuth (manual refresh token) Red X icon Not supported
Basic authentication (username/password) Red X icon Not supported
Basic authentication (API key) Red X icon Not supported
Basic authentication (service account JSON key) Red X icon 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:
  • 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 The steps to create a connection depend on the authentication method you choose.
Interface The steps to create a pipeline depend on the interface.
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, column selection, and row filtering. Supported configurations vary by connector. See Feature availability.

Start ingesting from Meta Ads

The following table provides an overview of the end-to-end Meta Ads ingestion flow, based on user type:

User Steps
Admin
  • Configure Meta Ads to enable authentication from Azure Databricks. See Set up Meta Ads as a data source.
  • Use Catalog Explorer to create a connection to Meta Ads so that non-admins can create pipelines. See Meta Ads.
Non-admin Use any supported interface to create a pipeline from an existing connection. See Ingest data from Meta Ads.
  • Last updated on