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Important
The PostgreSQL connector is in Public Preview. Contact your Azure Databricks account team to request access.
This page helps you understand the PostgreSQL ingestion workflow, including the factors that determine your setup approach and the steps involved for different user personas.
Important
Before you create a PostgreSQL ingestion pipeline, you must configure the source database directly in PostgreSQL: enable logical replication, create a replication user, and create publications and replication slots. Complete these tasks first. See Configure PostgreSQL for ingestion into Azure Databricks.
Feature availability
| Feature | Availability |
|---|---|
| UI-based pipeline authoring | |
| API-based pipeline authoring | |
| Declarative Automation Bundles | |
| Incremental ingestion | |
| Unity Catalog governance | |
| Orchestration using Databricks Workflows | |
| SCD type 2 | |
| API-based column selection and deselection | |
| API-based row filtering | |
| Automated schema evolution: New and deleted columns | |
| Automated schema evolution: Data type changes | |
| Automated schema evolution: Column renames | Treated as a new column (new name) and deleted column (old name). |
| Automated schema evolution: New tables | If you ingest the entire schema. See the limitations on the number of tables per pipeline. |
| Maximum number of tables per pipeline | 250 |
Authentication methods
| Authentication method | Availability |
|---|---|
| OAuth U2M | |
| OAuth M2M | |
| OAuth (manual refresh token) | |
| Basic authentication (username/password) | |
| Basic authentication (API key) | |
| Basic authentication (service account JSON key) |
What to know before you start
| Topic | Why it matters |
|---|---|
| Azure Databricks user persona | The workflow depends on your Azure Databricks user persona:
|
| Deployment environment | The source database configuration depends on the PostgreSQL deployment environment. |
| Authentication method | The steps to create a connection depend on the authentication method you choose. |
| Interface | The steps to create a connection, a gateway, and 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 PostgreSQL
The following table provides an overview of the end-to-end PostgreSQL ingestion workflow, based on user type:
| User | Steps |
|---|---|
| Admin |
|
| Non-admin | Use any supported interface to create a gateway and a pipeline. See Ingest data from PostgreSQL. |