Note
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Access to this page requires authorization. You can try changing directories.
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 Veeva Vault connector in Lakeflow Connect ingests standard objects (__v), custom objects (__c), system tables, and audit trail tables from Veeva Vault into Azure 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 Azure Databricks user persona, supported interfaces, ingestion frequency, and common patterns.
- Configure Veeva Vault for ingestion (Admins) — Set up Veeva Vault to authenticate with Azure Databricks.
- Create a Unity Catalog connection (Admins) — Create a connection in Catalog Explorer so non-admins can create pipelines.
- Create an ingestion pipeline (Admins or non-admins) — Select any supported interface and create a pipeline from an existing connection.