Google Workspace connector

Important

This feature is in Beta. To use it, a workspace admin must turn on Lakeflow Connect for Google Workspace from the Previews page. See Manage Azure Databricks previews.

The managed Google Workspace connector in Lakeflow Connect ingests audit activity from Google Workspace applications and services into Azure Databricks.

Feature availability

Feature	Availability
UI-based pipeline authoring	Supported
API-based pipeline authoring	Supported
Declarative Automation Bundles	Supported
Incremental ingestion	Supported
Unity Catalog governance	Supported
Orchestration using Databricks Workflows	Supported
API-based column selection and deselection	Supported
API-based row filtering	Not supported
SCD Type 2	Not supported
Automated schema evolution: New and deleted columns	Supported
Automated schema evolution: Data type changes	Not supported
Automated schema evolution: Column renames	Supported Treated as a new column (new name) and deleted column (old name).

Authentication methods

Authentication method	Availability
OAuth U2M	Supported
OAuth M2M	Not supported
Basic authentication (username/password)	Not supported

Ingest audit activity from Google Workspace

Set up the managed Google Workspace connector to ingest Google Workspace audit activity into Azure Databricks.

Note

Before starting, review the Azure Databricks user persona, supported interfaces, ingestion frequency, and common patterns.

1. Configure Google Workspace for ingestion (Admins): Set up Google Workspace to authenticate with Azure Databricks.
2. Create a Unity Catalog connection (Admins): Create a connection in Catalog Explorer to store credentials for Databricks to authenticate with Google Workspace.
3. Create an ingestion pipeline (Admins or non-admins): Select any supported interface and create a pipeline from an existing connection.