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Can a SQL Warehouse Pro be shared across multiple workspaces

jfid
New Contributor II

I'm currently using a SQL Warehouse Pro in one of my Databricks workspaces, and I’m trying to optimize costs. Since the Pro Warehouse can be quite expensive to run, I’d prefer not to spin up additional instances in each workspace.

Is there any way to share a single SQL Warehouse Pro instance across multiple Databricks workspaces?
Or is it required to create a separate warehouse in each workspace, even if the compute and data access needs are similar?

For context:

  • All workspaces are under the same account.

  • Unity Catalog is enabled.

1 ACCEPTED SOLUTION

Accepted Solutions

Stefan-Koch
Valued Contributor II

hi @jfid 

A SQL Warehouse Pro instance cannot be shared directly across multiple Databricks workspaces. Each workspace requires its own SQL Warehouse instance, even if the compute and data access needs are similar. This is because compute resources like SQL Warehouses are tied to individual workspaces and cannot be accessed across workspace boundaries.

However, since you have Unity Catalog enabled, you can centralize data access and governance across workspaces. Unity Catalog allows you to share data (catalogs, schemas, and tables) across multiple workspaces under the same account. This means you can manage data centrally while maintaining separate compute resources in each workspace

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1 REPLY 1

Stefan-Koch
Valued Contributor II

hi @jfid 

A SQL Warehouse Pro instance cannot be shared directly across multiple Databricks workspaces. Each workspace requires its own SQL Warehouse instance, even if the compute and data access needs are similar. This is because compute resources like SQL Warehouses are tied to individual workspaces and cannot be accessed across workspace boundaries.

However, since you have Unity Catalog enabled, you can centralize data access and governance across workspaces. Unity Catalog allows you to share data (catalogs, schemas, and tables) across multiple workspaces under the same account. This means you can manage data centrally while maintaining separate compute resources in each workspace

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