Databricks Releases
Databricks blog and Terraform provider releases. New features, breaking changes, security advisories and deprecations - each summarised in plain English and updated continuously.
Tracking 180 Databricks releases · Updated
- Databricks Python SDK Releases sdkdatadatabricksengineer ·
Databricks SDK for Python v0.123.0: API changes and breaking updates
Databricks SDK for Python version 0.123.0 introduces several new workspace-level services and API fields, including AI Gateway and expanded telemetry configuration. Notably, breaking changes affect the bundle deployments service with modified method signatures and removed fields, impacting how developers manage deployments. This release primarily affects users of the Databricks SDK for Python, particularly those working with bundle deployments or integrating AI Gateway.
breaking patch - Databricks Java SDK Releases sdkdatadatabricksengineer ·
Databricks SDK Java v0.135.0 Adds Catalog Enums, Includes Breaking Changes
Databricks SDK Java v0.135.0 introduces new enum values for catalog ownership, enhancing schema and table management. However, this release also contains breaking changes, including a modified `createDeployment()` method signature and the removal of the `deploymentId` field from the `CreateDeploymentRequest`. These changes require users of the Java SDK to update their code to accommodate the new API structure.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.164.0: API changes and breaking updates
Databricks SDK Go v0.164.0 introduces new enum values for catalog ownership and includes two breaking changes. Developers using the SDK must update their code to accommodate the reordered arguments in the `CreateDeployment` method and the removal of the `DeploymentId` field in the request. These changes primarily affect engineers and architects working with Databricks bundles and workspace deployments.
breaking patch - Databricks Java SDK Releases sdkdatabricksengineer ·
Databricks SDK for Java v0.134.0: New fields and one breaking change
Databricks SDK for Java v0.134.0 introduces several new fields across compute, jobs, ML, and Postgres integration, enhancing cluster configuration and schema management. However, it also includes a breaking change with the removal of the 'lifetime' field in the TimeWindow model for ML services. These updates primarily affect Java developers working with the Databricks platform, particularly those integrating with compute, ML workflows, or data synchronization features.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.163.0: New fields and breaking change
Databricks SDK Go v0.163.0 introduces several new fields across compute, jobs, ML, and PostgreSQL services, enhancing cluster configuration and ML tasks. Notably, the SDK removes the `Lifetime` field from `ml.TimeWindow`, which is a backwards-incompatible change requiring consumer action. These updates are primarily for Go developers working with the Databricks platform.
breaking patch - endoflife.date eoldatabricks-runtime ·
Databricks Runtime 13.3 reaches end of life in 30 days
Databricks Runtime 13.3 reaches end of life on 2026-08-22 (30 days from now).
deprecation - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.161.0: API changes and breaking updates
Databricks SDK Go version 0.161.0 introduces several new fields across various services, including jobs, machine learning, networking, and serving, enhancing functionality for users. However, it also includes breaking changes to IAMv2 methods and modifications to window duration fields in ML services, requiring developers to update their code. These updates affect users interacting with Databricks account and workspace IAM features, as well as those utilizing ML time window functionalities.
breaking patch - Databricks Python SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Python v0.122.0 Introduces New APIs and Breaking Changes
This release of the Databricks SDK for Python (v0.122.0) adds new methods for managing clean rooms and PostgreSQL configurations, along with numerous field additions across various services. Notably, it includes several breaking changes, particularly affecting IAM v2 and ML TimeWindow configurations, which may require adjustments in existing integrations. These updates are primarily relevant to developers and architects working with the Databricks platform and its associated APIs.
breaking patch - Databricks Java SDK Releases sdkmldatabricks ·
Databricks SDK for Java v0.132.0: API changes
Databricks SDK for Java version 0.132.0 introduces several API modifications, including a new field for pipeline connector options and changes to window duration requirements for ML components. These updates affect developers using the Java SDK for Databricks integrations, particularly those working with ML models or data pipelines.
breaking patch - Databricks Java SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Java v0.131.0 adds fields, includes breaking API changes
Databricks SDK Java version 0.131.0 introduces new fields across several services, including ML, Jobs, Networking, and Workspace. This release also contains breaking changes affecting IAM v2 client methods and the TimeWindow object in ML, requiring consumers to update their code. These updates are now generally available.
breaking patch - Databricks Python SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Python v0.121.0: API updates and breaking changes
Databricks SDK for Python version 0.121.0 introduces new fields and methods across various services, including workspace grants, disaster recovery, and machine learning aggregations. Notably, several breaking changes are implemented, such as making the 'role' field required for PostgreSQL database specs and removing fields related to secret browsing and distinct count aggregations. The release also includes improved documentation for authentication types, benefiting developers using the SDK.
breaking patch - Databricks Java SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Java v0.130.0 Adds Features, Includes Breaking Change
Databricks SDK Java v0.130.0 introduces several new fields and enum values across various services, enhancing capabilities for bundle deployments, cleanrooms, compute, disaster recovery, ML, and pipelines. A significant breaking change is the removal of the `codeSourcePath` field from `AiRuntimeTask` in the jobs service, requiring users to update their code if they rely on this field. This release is available now and impacts developers using the Java SDK.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.159.0: New fields, one breaking change
The Databricks SDK Go version 0.159.0 introduces new fields for disaster recovery and pipeline configurations, enhancing data resilience and pipeline management. However, it also removes the `CodeSourcePath` field from `AiRuntimeTask` in the jobs service, which is a breaking change requiring user code updates. This release impacts developers using the Go SDK for Databricks integration.
breaking patch - Databricks Java SDK Releases sdkdatadatabricksengineer ·
Databricks SDK Java v0.128.0: CDF Configs and Breaking IAM Changes
Databricks SDK Java version 0.128.0 introduces new methods for managing Change Data Feed (CDF) configurations via the workspace client. It also adds a `parent` field to connection objects and a `MINUTES` enum for job triggers. Crucially, this release includes breaking changes to the `internalId` field type for IAM entities (Groups, Service Principals, Users), requiring Java SDK users to update their code to adapt to the String type.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.157.0: New CDF methods, Parent field, and breaking ID changes
The Databricks SDK for Go version 0.157.0 introduces new methods for managing Change Data Feed (CDF) configurations for Postgres and adds a Parent field to catalog connection requests. It also includes breaking changes, modifying the `InternalId` field for IAM groups, service principals, and users to be a string type. These updates are relevant for developers using the Go SDK to interact with Databricks services, particularly those managing Postgres CDF or IAM entities.
breaking patch - endoflife.date eoldatabricks-runtime ·
Databricks Runtime 13.3 reaches end of life in 41 days
Databricks Runtime 13.3 reaches end of life on 2026-08-22 (41 days from now).
deprecation - Databricks Java SDK Releases sdkdatabricksengineer ·
Databricks SDK Java v0.126.0: API changes and breaking update
Databricks SDK Java version 0.126.0 introduces new API fields and a breaking change requiring the `role` field for `DatabaseDatabaseSpec`. This update is relevant for Java developers using the Databricks SDK, particularly those interacting with bundle deployments or PostgreSQL database specifications.
breaking patch - Databricks Go SDK Releases sdkdatadatabricksengineer ·
Databricks SDK Go v0.155.0: API updates and breaking change
Databricks SDK Go version 0.155.0 introduces an update to the bundle deployments resource with a new `UpdateTime` field. A significant breaking change requires the `Role` field to be mandatory for Postgres database specifications. These updates primarily affect Go developers using the Databricks SDK for managing Databricks resources.
breaking patch - Terraform Databricks Provider Releases terraforminfradatabricksgadeprecationengineer ·
Databricks Terraform Provider v1.121.0: Breaking Changes and New AI Features
Databricks Terraform provider version 1.121.0 introduces breaking changes to the `databricks_mws_ncc_private_endpoint_rule` resource, tightening read-only attributes and improving provisioning state visibility. It also adds new resources for AI Search and enhancements to cluster configurations. These changes primarily affect users managing Databricks infrastructure with Terraform, particularly those using the `mws_ncc_private_endpoint_rule` resource or looking to integrate with Databricks AI Search capabilities.
breaking patch - Databricks Java SDK Releases sdkdatadatabricksengineer ·
Databricks SDK for Java v0.124.0: API updates and breaking changes
Databricks SDK for Java version 0.124.0 introduces several API additions and modifications, including new fields for ML service configurations and updated workspace client methods. However, it also removes several fields across different services, such as `firstDistinctN`, `lastDistinctN`, `includeBrowse`, `browseOnly`, `externalSecretId`, and `groupName`, which may require consumers to update their existing code. This release focuses on enhancing existing functionalities while also incorporating breaking changes that necessitate careful review by developers using the Java SDK.
breaking patch
About Databricks release tracking on ReleaseBytes
Databricks platform releases, runtime versions and Terraform provider updates each have their own changelog. ReleaseBytes merges them into one feed with plain-English summaries, and its EOL tracker follows Databricks runtime support windows — including the Python and Spark versions each runtime pins.
Frequently asked questions
How often are Databricks release notes updated on ReleaseBytes? ›
Continuously. ReleaseBytes monitors the official Databricks release channels around the clock and publishes a plain-English summary of each announcement shortly after it lands.
What kinds of Databricks changes does ReleaseBytes track? ›
New features, enhancements, bug fixes, security advisories, breaking changes, deprecations and end-of-life announcements. Every item is tagged by type so you can filter to just the changes that need action.
How can I get alerts for new Databricks releases? ›
Set up a free email or Slack alert filtered to Databricks, subscribe to the weekly digest, or follow the RSS feed. Teams can also install the ReleaseBytes GitHub App or connect via MCP.
Where does the Databricks release data come from? ›
From the official sources: Databricks blog and Terraform provider releases. Every item links back to the original vendor announcement.