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Databricks SQL release notes

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This article lists new Databricks SQL features and improvements, along with known issues and FAQs.

Release process

Databricks releases updates to the Databricks SQL web application user interface on an ongoing basis, with all users getting the same updates rolled out over a short period of time.

In addition, Databricks typically releases new SQL warehouse compute versions regularly. Two channels are always available: Preview and Current.

Note

Releases are staged. Your Databricks account might not be updated with a new SQL warehouse version or Databricks SQL feature until a week or more after the initial release date.

Note

Databricks SQL Serverless is not available in Azure China. Databricks SQL is not available in Azure Government regions.

Channels

Channels let you choose between the Current SQL warehouse compute version or the Preview version. Preview versions let you try out functionality before it becomes the Databricks SQL standard. Take advantage of preview versions to test your production queries and dashboards against upcoming changes.

Typically, a preview version is promoted to the current channel approximately two weeks after being released to the preview channel. Some features, such as security features, maintenance updates, and bug fixes, may be released directly to the current channel. From time to time, Databricks may promote a preview version to the current channel on a different schedule. Each new version will be announced in the following sections.

To learn how to switch an existing SQL warehouse to the preview channel, see Preview Channels. The features listed in the user interface updates sections are independent of the SQL Warehouse compute versions described in the Channels section of the release notes.

Available Databricks SQL versions

Current channel: Databricks SQL version 2024.40 Preview channel: Databricks SQL version 2024.40

Known issues

  • Reads from data sources other than Delta Lake in multi-cluster load balanced SQL endpoints can be inconsistent.
  • Delta tables accessed in Databricks SQL upload their schema and table properties to the configured metastore. If you are using an external metastore, you will be able to see Delta Lake information in the metastore. Delta Lake tries to keep this information as up-to-date as possible on a best-effort basis. You can also use the DESCRIBE <table> command to ensure that the information is updated in your metastore.
  • Databricks SQL does not support zone offsets like ‘GMT+8’ as session time zones. The workaround is to use a region based time zone https://en.wikipedia.org/wiki/List_of_tz_database_time_zones) like ‘Etc/GMT+8’ instead. See SET TIME ZONE for more information about setting time zones.

Frequently asked questions (FAQ)

Use the following list to learn the answers to common questions.

How are Databricks SQL workloads charged?

Databricks SQL workloads are charged according to the Standard Jobs Compute SKU.

Where do SQL warehouses run?

Classic and pro SQL warehouses are created and managed in your Azure account. SQL warehouses manage SQL-optimized clusters automatically in your account and scale to match end-user demand.

Serverless SQL warehouses, on the other hand, use compute resources in your Databricks account. serverless SQL warehouses simplify SQL warehouse configuration and usage and accelerate launch times. The serverless option is available only if it has been enabled for the workspace. For more information, see Serverless compute plane.

Can I use SQL warehouses from a notebook in the same workspace?

Yes. To learn how to attach a notebook to a SQL warehouse, see Use a notebook with a SQL warehouse.

I have been granted access to data using a cloud provider credential. Why can’t I access this data in Databricks SQL?

In Databricks SQL, all access to data is subject to data access control, and an administrator or data owner must first grant you the appropriate privileges.