Veeva Vault 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 Veeva Vault connector in Lakeflow Connect ingests standard objects (__v), custom objects (__c), system tables, and audit trail tables from Veeva Vault into Databricks. The connector uses Veeva's Direct Data API to access your Vault instance.

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	Not 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	Not supported Requires a full refresh.

Authentication methods

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

Ingest from Veeva Vault in 3 steps

note

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

1. Configure Veeva Vault for ingestion (Admins) — Set up Veeva Vault 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.