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, reliability, performance, and security of the Databricks platform.

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

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

15.4 LTS

3.5.0

Aug 19, 2024

Aug 19, 2027

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

Dec 19, 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

16.0

3.5.0

Nov 11, 2024

May 11, 2025

15.4 LTS

3.5.0

Aug 19, 2024

Aug 19, 2027

15.3

3.5.0

Jun 24, 2024

Dec 24, 2024

15.2

3.5.0

May 22, 2024

Nov 22, 2024

14.3 LTS

3.5.0

Feb 1, 2024

Feb 1, 2027

14.1

3.5.0

Oct 11, 2023

Feb 12, 2025

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

Dec 19, 2024

MLflow-Databricks Runtime compatibility matrix

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

Databricks Runtime ML version

MLflow version

16.0

2.15.1

15.4 LTS

2.13.1

15.3

2.11.3

15.2

2.11.3

14.3 LTS

2.9.2

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

16.0

0.7.x

None

15.4 LTS

0.6.x

None

15.3

0.5.x

None

15.2

0.4.x

None

14.3 LTS

0.2.x

None

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

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 End-of-support Databricks Runtime release notes. The unsupported Databricks Runtime versions have been retired and might not be updated.