Del via

Azure Databricks release notes

The following sections organize Azure Databricks release notes by release type, including Databricks Runtime releases, platform releases, and feature-specific releases such as Databricks SQL, Lakeflow Declarative Pipelines, and serverless compute.

Databricks Runtime release notes

The following table provides links to release notes for the latest Databricks Runtime releases.

Long-term support (LTS) runtimes Machine learning (ML) long-term support runtimes Latest Databricks Runtimes Latest Databricks Runtimes for ML

For a complete list of supported runtimes, version compatibilities, and available Beta releases, see Databricks Runtime release notes versions and compatibility.

Azure Databricks platform release notes

Release notes for the latest Azure Databricks platform features, improvements, and fixes are found in the following articles:

For all platform release notes, see Azure Databricks platform release notes.

Feature-specific release notes

The following Azure Databricks features have their own dedicated release note articles:

Feature Description
AI/BI A business intelligence product that includes dashboards for visualization and reporting, plus Genie for conversational analytics.
Databricks SQL The collection of services supporting data warehousing and querying features on the Databricks Data Intelligence Platform.
Databricks dev-tools and SDKs IDE extensions, plugins, command-line interfaces, SDKs, and SQL connectors and drivers.
Databricks Connect Connect IDEs, notebook servers, and other custom applications to Databricks compute.
Databricks Asset Bundles Databricks Assets Bundles are an infrastructure-as-code (IaC) approach to managing Databricks projects.
Lakeflow Declarative Pipelines A declarative framework designed to simplify the creation of reliable and maintainable extract, transform, and load (ETL) pipelines.
Serverless compute Run your Databricks workloads without configuring and deploying infrastructure.
Databricks feature engineering Create, read, and write feature tables. Train models on feature data. Publish feature tables to online stores for real-time serving.

Databricks release notes feed

The Databricks documentation site provides an RSS feed that contains updates to the product and other feature release notes. The feed conforms to the RSS feed specification and can be used with any feed reader or client that can consume an RSS feed. Feed readers offer features such as filtering of feed items and email notifications when the feed is updated, so that you can stay informed of the latest Databricks releases.

The Databricks documentation feed is available at the following URL. It is currently only available in English.

https://learn.microsoft.com/en-us/azure/databricks/feed.xml

Each item in the Databricks documentation feed contains information about one release note, including the following information:

  • The date of the release
  • A summary of the release
  • A link to the release note
  • A longer description of the release that often includes links to additional information
  • Categories, such as an applicable feature area

Understand the release process

For information about the release process and upcoming features, see the following articles: