Aha! 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 Aha! connector in Lakeflow Connect ingests ideas, products, tasks, and related product-management records from Aha! into 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 Lakeflow Jobs	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	Not supported Requires a full refresh.

Authentication methods

Authentication method	Availability
OAuth U2M	Not supported
OAuth M2M	Not supported
Basic authentication (username/password)	Not supported
Basic authentication (API key)	Supported Aha! personal API key.

Ingest from Aha! in 3 steps

note

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

1. Configure Aha! for ingestion (Admins) — Set up Aha! 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.