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 Blog blogdataanalyticsdatabricksengineermedia ·
NBCUniversal Migrates to Databricks Lakehouse for Scalable Analytics
NBCUniversal successfully migrated its data infrastructure to the Databricks Lakehouse Platform, achieving a 30% cost reduction by switching to dedicated job compute. This move enables independent scaling of data pipelines, faster job completion, and meets Service Level Agreements. The migration impacts data analysts, engineers, and scientists by providing a unified platform for advanced ML model development and real-time analytics, with a phased, partner-led implementation by EXL minimizing disruption.
feature patch announcement - 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 Go SDK Releases sdkaidatabricksengineer ·
Databricks Go SDK v0.167.0 Adds Cloud Provider Auth Fields
The Databricks Go SDK has been updated to version 0.167.0, introducing new fields for cloud provider authentication within the catalog service. These additions allow for more direct configuration of authentication methods with services like Amazon Bedrock and Azure OpenAI, impacting engineers and architects working with Databricks integrations. The update enhances flexibility for securing access to AI model providers.
patch - Databricks Java SDK Releases sdkaidatabricksengineer ·
Databricks SDK Java v0.138.0 Adds Model Provider Config Fields
Version 0.138.0 of the Databricks SDK for Java introduces new fields to model provider configurations, enhancing integration capabilities. These changes allow for more direct configuration of specific cloud provider details, impacting developers using the SDK for MLOps and AI model deployment. The updates are now available in the latest SDK release.
patch - Terraform Databricks Provider Releases terraforminfradatabricksengineerdatabricks-unity-catalog ·
Databricks Terraform Provider v1.123.0: Improved Plan Validation, Delta Sharing, MLflow, and Bug Fixes
Databricks Terraform provider version 1.123.0 shifts workspace ID validation from plan to apply, resolving false-positive plan failures for certain configurations. It also introduces a data source for Delta Sharing recipients and enhances MLflow experiment tracing with Unity Catalog integration. Several bug fixes address issues with view column comments and access control rule set drift detection, impacting users managing Databricks resources via Terraform.
patch - Databricks Java SDK Releases sdkaidatabricksengineer ·
Databricks SDK Java v0.137.0 adds AI Gateway and deployment fields
Databricks SDK Java version 0.137.0 introduces new features and enhancements to the bundle deployment service and adds a new AI Gateway service. These updates provide expanded capabilities for managing AI services and improve the granularity of information available for deployment tracking. The release is intended for developers and architects working with Databricks integrations.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Go v0.166.0 Enhances Workspace Services
Databricks has released version 0.166.0 of its Go SDK, introducing new workspace-level services and enhancing existing ones. Key additions include an AiGateway service and an UpdateOperation method for BundleDeployments, along with expanded fields for deployment and operation details. These changes provide developers with more granular control and visibility over workspace resources, particularly for deployment management.
patch - Databricks Java SDK Releases sdkdatabricksengineer ·
Databricks SDK Java v0.136.0 Updates
Databricks SDK Java has been updated to version 0.136.0, introducing new API capabilities. These changes include the addition of a method for patching telemetry configurations and new fields for schema specifications and SQL alerts. The updates primarily affect developers using the Java SDK to interact with Databricks services like serving endpoints and pipelines.
patch - Databricks Go SDK Releases sdkdatadatabricksengineer ·
Databricks SDK for Go v0.165.0 Adds New API Methods
Databricks SDK for Go version 0.165.0 introduces several new API methods and fields to enhance functionality for workspace telemetry, data pipelines, and SQL alerts. These updates provide developers with more granular control and expanded capabilities within the Databricks platform. The changes are available immediately for users of the Go SDK.
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 Java SDK Releases sdkinfradatabricks ·
Databricks SDK Java v0.133.0 Adds Fields to Workspace, Job, and Serving APIs
Databricks SDK Java version 0.133.0 introduces new fields across several service APIs, including `effectiveEntitlements` for workspace assignments, `serverlessComputeId` for job clusters, and `tableNames` along with `telemetryProfileId` for serving telemetry configuration. These updates enhance the SDK's ability to manage and configure Databricks resources. This is a patch release, affecting developers using the Java SDK for Databricks integration.
patch - Databricks Go SDK Releases sdkgovernancedatabricksengineer ·
Databricks SDK for Go v0.162.0 Adds IAM and Jobs Fields
The Databricks SDK for Go version 0.162.0 introduces new fields to enhance IAM and job cluster configurations. It adds `EffectiveEntitlements` for `WorkspaceAssignmentDetail` and `ServerlessComputeId` for `JobCluster`, providing more granular control and visibility into workspace assignments and serverless compute options. These updates are relevant for Go developers integrating with Databricks APIs, offering expanded capabilities for managing entitlements and configuring serverless job clusters.
patch - 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 - Terraform Databricks Provider Releases terraforminfradatabricksengineer ·
Databricks Terraform Provider v1.122.0 adds Postgres CDF, fixes view column comments
Version 1.122.0 of the Databricks Terraform provider introduces new resources for managing PostgreSQL Change Data Feed (CDF) configurations and their statuses. This release also resolves a bug that prevented updates to column comments on views, a common issue for engineers managing SQL objects via Terraform. The fix ensures that column comment changes on views are applied correctly, preventing perpetual diffs for affected users.
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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.