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Data sources

Databricks Unity Catalog

Connect Databricks Unity Catalog to Queringo. Setup, fields, testing, editing, and alternatives.

Updated May 27, 2026

Governed catalog over the lakehouse.

Connect Databricks Unity Catalog form in Queringo

At a glance

CategoryData lakes
AuthToken
PlanScale and above

Setup

  1. Open Connect source

    In the app, go to Data sources and choose Connect source. Open the Data lakes tab and select Databricks Unity Catalog.

  2. Paste your access token

    In the provider's admin area, generate an API access token with read access, then paste it into the Databricks Unity Catalog connection form.

  3. Save the connection

    Queringo tests the connection before saving, then discovers the schema. PII is flagged and masked by default during discovery.

Where to find these in your provider

  1. In Databricks, ensure the workspace is enabled for Unity Catalog and you have READ on the catalog you want to expose.
  2. Generate a personal access token from your user settings (Developer → Access tokens).
  3. Note your workspace hostname and the catalog name.
  4. Paste the hostname, catalog, and token into the connection form.

Test the connection

Queringo runs a connection test as part of saving. If it fails, the error message indicates what to check (credentials, network reachability, or scope). From Data sources, you can re-run Test connection on the source row any time, for example after rotating a secret or changing network rules.

Edit or rotate

To change connection details (host, port, or database), open the source from Data sources and edit it. To swap only the secret (password, key file, or token), use Rotate credentials so existing dashboards and alerts keep working. See Rotating credentials.

Reference

Suggest a different connector

Don't see what you need? In the Connect a data source picker, choose Request it. Queringo bundles votes from every workspace asking for the same one and prioritizes accordingly.

What's next

For the category overview and shared options, see Data lakes. To keep sources healthy, see Managing sources.