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The Databricks integration is in Beta and is enabled per workspace. Before you can register tables, an IT administrator must prepare Databricks and connect the SQL warehouse in Speckle. If your project’s Integrations does not show Databricks, ask your IT administrator to follow Enable Databricks integration.

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Setup

These steps assume an IT administrator has already connected a Databricks SQL warehouse in Speckle. If it hasn’t, your IT administrator must complete Enable Databricks integration first.
1

Browse to your table

In Speckle, open your project’s Integrations > Databricks, expand catalog > schema, and find the table you want. Only catalogs, schemas, and tables your IT administrator has granted access to will appear. Select a table to preview its rows.
Browsing and previewing a Databricks table
You can preview the table rows before registering.
2

Choose the columns and register

Pick the columns to include — only the columns you choose are ever read or cached — then select Register. Speckle validates access, reads the selected columns, and builds the first snapshot. The table now appears as a registered data source.
Registering a Databricks table as a data source
The table appears as a registered data source in your project.
Registered data sources are available to Speckle tools such as the AI chat, where you can query the table and combine it with your model data. See Intelligence Dashboards for analytics and data tools. Help shape this workflow on the Databricks integration study.

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How snapshots are stored and refreshed

When you register a table, Speckle reads the columns you selected and stores a cached snapshot in your workspace’s object storage. Tools query the snapshot rather than your live warehouse.
  • Automatic refresh. A snapshot is rebuilt from the warehouse when it goes stale (default freshness window: 24 hours), the next time it’s used.
  • Manual refresh. You can force an immediate refresh from the registered table’s controls — useful right after the source data changes.
  • Disconnecting. If your IT administrator removes the Databricks connection, registered sources keep serving their last snapshot read-only. Reconnecting the same warehouse relinks them and resumes refreshing.

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FAQ

Only the columns you select when registering a table. Columns you don’t include are never queried or cached.
Speckle stores a snapshot of your registered columns and refreshes it on a schedule. See How snapshots are stored and refreshed.
Your registered sources keep serving their last cached snapshot read-only, so existing tools don’t break. If your IT administrator reconnects the same warehouse, refreshing resumes.
No. The integration is read-only — Speckle issues SELECT queries only and never writes, updates, or deletes data in Databricks.
Last modified on June 9, 2026