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
- Terraform Databricks Provider Releases terraforminfradatabricksdeprecationengineer ·
Databricks Terraform Provider v1.120.0: New Postgres API resource, SDKv2 deprecation
Databricks Terraform Provider v1.120.0 introduces a new resource for the PostgreSQL Data API and deprecates older SDKv2 fallback implementations for several resources and data sources. This change affects users managing Databricks resources with Terraform, particularly those relying on the older SDKv2 fallbacks, who should transition to the default Plugin Framework implementations to avoid issues in future releases. The release also includes bug fixes for permissions drift and application authorization.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.151.0 API Change
The Databricks SDK for Go version 0.151.0 introduces a new `Spec` field to the `WorkspaceBaseEnvironment` type. This API change is relevant for developers using the Go SDK to interact with Databricks environments. The update provides additional configuration options for workspace environments.
patch - Databricks Python SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Python v0.119.0 adds policy compliance and DR features
Databricks SDK Python version 0.119.0 introduces new features and API enhancements, including expanded policy compliance capabilities and disaster recovery support. These updates allow for more granular control over cluster enforcement and asset replication for disaster recovery scenarios. The release impacts developers using the Python SDK, particularly those working with workspace compute policies and disaster recovery configurations.
breaking patch - Terraform Databricks Provider Releases terraforminfradatabricksengineer ·
Databricks Terraform Provider v1.119.0 Updates Documentation and CI
Databricks Terraform Provider v1.119.0 updates documentation to clarify workspace binding applicability for catalog objects. It also introduces an internal change to improve CI by running unit tests offline using a pre-warmed Go module cache. This aims to resolve authentication issues for certain PRs and speed up the testing process. These changes primarily affect engineers and CI/CD practitioners working with the Databricks Terraform provider.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.150.0: API additions, policy compliance, and breaking change
Databricks SDK Go version 0.150.0 introduces new methods and fields for managing cluster policy compliance, enhancing disaster recovery capabilities, and fixing a user agent bug. It also includes a breaking change related to workspace asset replication. This release affects developers using the Go SDK for Databricks automation and management.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.148.0 Adds Meta-Harness Dimension and New Compute Size
The Databricks SDK for Go version 0.148.0 introduces a new user-agent dimension to report the meta-harness, providing better visibility into its usage. Additionally, it adds an 'Xlarge' compute size option for applications. These changes are available now for Go developers working with Databricks.
patch - Terraform Databricks Provider Releases terraformaiinfragcpdatabricksengineer ·
Databricks Terraform Provider v1.118.0: New AI Search resources, bug fixes
Databricks Terraform provider version 1.118.0 introduces new resources for AI Search endpoints and indexes, enhancing AI capabilities. This release also addresses several bugs, including issues with instance pools, entitlements, and workspace configurations on GCP, improving stability and reliability for users managing Databricks resources via Terraform. The update also includes documentation improvements for job tasks and rewrites exporter logging.
patch - Databricks Java SDK Releases sdkinfradatabricks ·
Databricks SDK for Java v0.121.0 adds serverless compute option
The latest release of the Databricks SDK for Java, version 0.121.0, introduces the `serverlessComputeId` field to several pipeline-related requests and specifications. This enhancement allows users to specify serverless compute configurations when managing pipelines. The update is relevant for developers working with Databricks pipelines in Java, enabling more flexible deployment options.
patch - Databricks Java SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Java v0.120.0: API Additions and Breaking Change
Databricks SDK Java version 0.120.0 introduces new methods for managing Postgres data APIs and adds several fields to compute and database specifications. A significant breaking change modifies the `resourceId` field in the `Operation` class to be optional. These updates are relevant for developers using the Java SDK to interact with Databricks services, particularly those managing compute resources or database integrations.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.145.0: Bug fixes and API enhancements
Databricks SDK Go version 0.145.0 includes bug fixes for tag policy routing and several API changes, including a breaking change to the `ResourceId` field in bundle deployments. These updates affect developers working with tags, bundle deployments, and data catalog connections. The release also introduces new fields for vector indexes and adds a new connection type.
breaking patch - Databricks Python SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Python v0.117.0
Databricks SDK for Python version 0.117.0 introduces new fields for Synced Tables and makes a breaking change to the `resource_id` field in `Operation`. It also includes significant bug fixes for token caching and lazy initialization of `WorkspaceClient.dbutils` to improve performance and stability, particularly in Spark Connect environments. The release also declares `urllib3` as an explicit dependency.
breaking patch - Databricks Java SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Java v0.119.0: New API Packages and Breaking Changes
Databricks SDK Java version 0.119.0 introduces new API packages for AI Search and Bundle Deployments, alongside numerous field additions across various services. Notably, it removes the `com.databricks.sdk.service.bundle` package and its corresponding workspace client service, which are breaking changes. These updates primarily affect developers integrating with Databricks services via the Java SDK, requiring attention to the removal of the bundle service.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Go v0.142.0: New Services and Breaking Changes
Databricks SDK for Go version 0.142.0 introduces new packages for AI Search and Bundle Deployments, along with numerous new fields across various services like Catalog, ML, and Vector Search. This release also includes breaking changes by removing the `bundle` package and its associated workspace-level service. These updates affect Go developers utilizing the Databricks SDK, particularly those working with AI features, deployment pipelines, or relying on the deprecated bundle functionality.
breaking patch - Terraform Databricks Provider Releases terraforminfradatabricksengineer ·
Databricks Terraform Provider v1.117.0: Fix External Location File Events
Databricks Terraform Provider version 1.117.0 fixes a bug in `databricks_external_location` where setting `enable_file_events` to `false` was ignored. This change ensures that when explicitly set to false, the provider now correctly sends this configuration to the Databricks API, preventing unexpected default behavior for file event monitoring. The fix targets users managing external locations via Terraform, ensuring their configuration for file events is respected.
patch - Databricks Java SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Java v0.115.0 adds deployment mode fields
Databricks SDK Java version 0.115.0 introduces new fields related to deployment mode to the `Deployment` and `Version` classes within the bundle service. It also adds connectivity fields to the `Setting` class in the settingsv2 service. These changes enhance configuration and management capabilities for Databricks deployments.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Go v0.141.0 Adds Bundle Deployment Options
Databricks SDK for Go version 0.141.0 introduces new fields to enhance bundle deployment configurations and settings management. These updates allow for more granular control over deployment modes and collaboration platform connectivity, impacting developers using the Go SDK for Databricks. The changes are available in the latest SDK release.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Go v0.140.0: Enhanced Workspace Addressing and API Features
Databricks SDK for Go version 0.140.0 introduces an improved workspace addressing mechanism using `X-Databricks-Workspace-Id` for API calls, enhancing the unification initiative. It also adds several new API fields and methods, including `UpdateTokenManagement` and fields for job and pipeline deployments, benefiting developers working with Databricks workspaces and configurations.
patch - Databricks Python SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Python v0.113.0
Databricks SDK for Python v0.113.0 introduces internal workspace addressing changes and adds new API methods for feature engineering and token management. It also introduces several new fields related to job deployments, pipeline tasks, and token settings, while removing two fields from the postgres service. These changes affect developers interacting with Databricks services programmatically, with some breaking changes requiring attention.
breaking patch - Terraform Databricks Provider Releases terraforminfragcpdatabricksgaengineer ·
Databricks Terraform Provider v1.116.0 Adds Agent Bricks Permissions, Principal IDs
Databricks Terraform Provider v1.116.0 introduces management of Git credentials for service principals and permissions for Agent Bricks resources. This release addresses several bugs, including issues with metastore updates, UC object destruction, library handling, and vector search index timeouts. These updates are relevant for engineers and architects managing Databricks infrastructure via Terraform.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Go v0.139.0: Feature Engineering API and breaking changes
Databricks SDK for Go version 0.139.0 introduces new methods for managing Feature Engineering streams and adds parameters to job and pipeline configurations. This release also includes breaking changes with the removal of `CatalogId` and `SyncedTableId` fields from PostgreSQL catalog status types, which may require users to update their integrations. The update is relevant for Go developers working with the Databricks platform.
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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.