Pendo 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 Pendo connector in Lakeflow Connect allows you to ingest product analytics data from Pendo into Databricks.

Feature availability

Feature	Availability
UI-based pipeline authoring	Supported
API-based pipeline authoring	Supported
Declarative Automation Bundles	Supported
Incremental ingestion	Not supported All tables are refreshed on each pipeline update.
Unity Catalog governance	Supported
Orchestration using Databricks Workflows	Supported
SCD type 2	Supported
API-based 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 Requires a full refresh.
Automated schema evolution: New tables	Supported If you ingest the entire schema.

Authentication methods

Authentication method	Availability
OAuth U2M	Not supported
OAuth M2M	Not supported
Basic authentication (username/password)	Not supported
Basic authentication (API key)	Supported Pendo API Integration Key.

Ingest from Pendo in 3 steps

note

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

Start ingesting from Pendo

1. Configure Pendo for ingestion (Admins) — Set up Pendo to authenticate with Databricks.
2. Create a Unity Catalog connection (Admins) — Create a connection in Catalog Explorer so non-admins can create pipelines.
3. Create an ingestion pipeline (Admins or non-admins) — Select any supported interface and create a pipeline from an existing connection.