Databricks Runtime release notes versions and compatibility

This article lists all Databricks Runtime releases and the schedule for supported releases. Each Databricks Runtime version includes updates that improve the usability, performance, and security of big data analytics.

To learn about Databricks Runtime support lifecycle, generally available releases, and Beta releases, see Databricks runtime support lifecycles. For information on maintenance updates issued for Databricks Runtime releases, see Databricks Runtime maintenance updates.

Databricks Runtime versions comparison tool

For information on migrating between Databricks Runtime versions, see the Databricks Runtime migration guide.

Supported Databricks Runtime LTS releases

The following table lists supported Databricks Runtime long-term support (LTS) version releases in addition to the Apache Spark version, release date, and end-of-support date. For optimal lifespan, use a Databricks Runtime LTS version.

Note

LTS means this version is under long-term support. See Databricks Runtime LTS version lifecycle.

Version

Variants

Apache Spark version

Release date

End-of-support date

14.3 LTS

3.5.0

Feb 1, 2024

Feb 1, 2027

13.3 LTS

3.4.1

Aug 22, 2023

Aug 22, 2026

12.2 LTS

3.3.2

Mar 1, 2023

Mar 1, 2026

11.3 LTS

3.3.0

Oct 19, 2022

Oct 19, 2025

10.4 LTS

3.2.1

Mar 18, 2022

Mar 18, 2025

9.1 LTS

3.1.2

Sep 23, 2021

Sep 23, 2024

All supported Databricks Runtime releases

The following table lists the Apache Spark version, release date, and end-of-support date for supported Databricks Runtime releases. For optimal lifespan, use a Databricks Runtime LTS version.

Version

Variants

Apache Spark version

Release date

End-of-support date

15.2

3.5.0

May 22, 2024

Nov 22, 2024

15.1

3.5.0

Apr 30, 2024

Oct 30, 2024

15.0

3.5.0

Mar 22, 2024

May 31, 2024

14.3 LTS

3.5.0

Feb 1, 2024

Feb 1, 2027

14.2

3.5.0

Nov 22, 2023

Oct 1, 2024

14.1

3.5.0

Oct 11, 2023

Oct 1, 2024

13.3 LTS

3.4.1

Aug 22, 2023

Aug 22, 2026

12.2 LTS

3.3.2

Mar 1, 2023

Mar 1, 2026

11.3 LTS

3.3.0

Oct 19, 2022

Oct 19, 2025

10.4 LTS

3.2.1

Mar 18, 2022

Mar 18, 2025

9.1 LTS

3.1.2

Sep 23, 2021

Sep 23, 2024

MLflow-Databricks Runtime compatibility matrix

This section lists Databricks Runtime ML versions and their respective MLflow versions.

Databricks Runtime ML version

MLflow version

15.2

2.11.3

15.1

2.10.2

15.0

2.10.2

14.3 LTS

2.9.2

14.2

2.8.0

14.1

2.7.1

13.3 LTS - 14.0

2.5.0

12.2 LTS

2.1.1

11.3 LTS

1.29.0

10.4 LTS

1.24.0

9.1 LTS

1.20.2

Feature Engineering compatibility matrix

This section lists Databricks Runtime ML versions and their respective Feature Engineering and Workspace Feature Store client versions.

Databricks Runtime ML version

databricks-feature-engineering version

databricks-feature-store version

15.2

0.4.x

None

15.1

0.3.x

None

15.0

0.3.x

None

14.3 LTS

0.2.x

None

14.2

0.1.x

0.16.1

14.1

0.1.x

0.15.1

13.3 LTS

0.1.x

0.14.1

12.2 LTS

Not supported

0.10.0

11.3 LTS

Not supported

0.7.0 (requires MLflow < 2.0)

10.4 LTS

Not supported

0.3.8 (requires MLflow < 2.0)

9.1 LTS

Not supported

0.3.4 (requires MLflow < 2.0)

Apache Spark migration guidance

You can find Spark-specific migration information in the Apache Spark documentation. The migration information for each Spark version can be found at a URL like the following:

https://spark.apache.org/docs/<version>/migration-guide.html.

Replace <version> with the Spark version included in the Databricks Runtime version you’re migrating to. For example, the URL with migration information for Spark 3.5.0, included in Databricks Runtime 14.3 LTS, is https://spark.apache.org/docs/3.5.0/migration-guide.html.

Beta releases

There are no Databricks Runtime Beta releases at this time.

Unsupported releases

For information on unsupported Databricks Runtime version release notes, see Unsupported Databricks Runtime release notes. The unsupported Databricks Runtime versions have been retired and might not be updated.