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Databricks SQL release notes

The following Databricks SQL features and improvements were released in 2025.

July 2025​

Preset date ranges for parameters in the SQL editor​

July 31, 2025

In the new SQL editor, you can now choose from preset date ranges—such as This week, Last 30 days, or Last year when using timestamp, date, and date range parameters. These presets make it faster to apply common time filters without manually entering dates.

Inline execution history in SQL editor​

July 24, 2025

Inline execution history is now available in the new SQL editor, allowing you to quickly access past results without re-executing queries. Easily reference previous executions, navigate directly to past query profiles, or compare run times and statuses—all within the context of your current query.

Databricks SQL version 2025.20 is now available in Current​

July 17, 2025

Databricks SQL version 2025.20 is rolling out in stages to the Current channel. For features and updates in this release, see 2025.20 features.

SQL editor updates​

July 17, 2025

  • Improvements to named parameters: Date-range and multi-select parameters are now supported.

  • Updated header layout in SQL editor: The run button and catalog picker have moved to the header, creating more vertical space for writing queries.

Git support for alerts​

July 17, 2025

You can now use Databricks Git folders to track and manage changes to alerts. To track alerts with Git, place them in a Databricks Git folder. Newly cloned alerts only appear in the alerts list page or API after a user interacts with them. They have paused schedules and need to be explicitly resumed by users.

Databricks SQL version 2025.20 is now available in Preview​

July 3, 2025

Databricks SQL version 2025.20 is now available in the Preview channel. Review the following section to learn about new features and behavioral changes.

SQL procedure support​

SQL scripts can now be encapsulated in a procedure stored as a reusable asset in Unity Catalog. You can create a procedure using the CREATE PROCEDURE command, and then call it using the CALL command.

Set a default collation for SQL Functions​

Using the new DEFAULT COLLATION clause in the CREATE FUNCTION command defines the default collation used for STRING parameters, the return type, and STRING literals in the function body.

Recursive common table expressions (rCTE) support​

SAP Databricks now supports navigation of hierarchical data using recursive common table expressions (rCTEs). Use a self-referencing CTE with UNION ALL to follow the recursive relationship.

ANSI SQL enabled by default​

The default SQL dialect is now ANSI SQL. ANSI SQL is a well-established standard and will help protect users from unexpected or incorrect results. Read the Databricks ANSI enablement guide for more information.

Support ALL CATALOGS in SHOW SCHEMAS​

The SHOW SCHEMAS syntax is updated to accept the following syntax:

SHOW SCHEMAS [ { FROM | IN } { catalog_name | ALL CATALOGS } ] [ [ LIKE ] pattern ]

When ALL CATALOGS is specified in a SHOW query, the execution iterates through all active catalogs that support namespaces using the catalog manager (DsV2). For each catalog, it includes the top-level namespaces.

The output attributes and schema of the command have been modified to add a catalog column indicating the catalog of the corresponding namespace. The new column is added to the end of the output attributes, as shown below:

Previous output

| Namespace        |
|------------------|
| test-namespace-1 |
| test-namespace-2 |

New output

| Namespace        | Catalog        |
|------------------|----------------|
| test-namespace-1 | test-catalog-1 |
| test-namespace-2 | test-catalog-2 |

Liquid clustering now compacts deletion vectors more efficiently​

Delta tables with Liquid clustering now apply physical changes from deletion vectors more efficiently when OPTIMIZE is running.

Allow non-deterministic expressions in UPDATE/INSERT column values for MERGE operations​

SAP Databricks now allows the use of non-deterministic expressions in updated and inserted column values of MERGE operations. However, non-deterministic expressions in the conditions of MERGE statements are not supported.

For example, you can now generate dynamic or random values for columns:

MERGE INTO target USING source
ON target.key = source.key
WHEN MATCHED THEN UPDATE SET target.value = source.value + rand()

This can be helpful for data privacy by obfuscating actual data while preserving the data properties (such as mean values or other computed columns).

Support VAR keyword for declaring and dropping SQL variables​

SQL syntax for declaring and dropping variables now supports the VAR keyword in addition to VARIABLE. This change unifies the syntax across all variable-related operations, which improves consistency and reduces confusion for users who already use VAR when setting variables.

June 2025​

Databricks SQL Serverless engine upgrades​

June 11, 2025

The following engine upgrades are now rolling out globally, with availability expanding to all regions over the coming weeks.

  • Lower latency: Mixed workloads now run faster, with up to 25% improvement. The upgrade is automatically applied to serverless SQL warehouses with no additional cost or configuration.
  • Predictive Query Execution (PQE): PQE monitors tasks in real time and dynamically adjusts query execution to help avoid skew, spills, and unnecessary work.
  • Photon vectorized shuffle: Keeps data in compact columnar format, sorts it within the CPU's high-speed cache, and processes multiple values simultaneously using vectorized instructions. This improves throughput for CPU-bound workloads such as large joins and wide aggregation.

User interface updates​

June 5, 2025

  • Query insights: Visiting the Query History page now emits the listHistoryQueries event. Opening a query profile now emits the getHistoryQuery event.
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