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 181 Databricks releases · Updated
- 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 sdkdatadatabricksengineer ·
Databricks SDK Go v0.146.0 Adds Postgres API Methods, Azure Compute Attribute
Databricks SDK Go version 0.146.0 introduces new methods for managing Postgres instances at the workspace level, including create, delete, get, and update operations. It also adds a `CapacityReservationGroup` field to Azure compute attributes. These enhancements aim to streamline cloud resource management for Databricks users working with Postgres and Azure infrastructure.
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 Go SDK Releases sdkdatadatabricksengineer ·
Databricks SDK Go v0.144.0 Adds TypeOverrides
Databricks SDK Go version 0.144.0 introduces new TypeOverrides fields for database.SyncedTableSpec and postgres.SyncedTableSyncedTableSpec. This enhancement allows for more granular control over table type configurations within the SDK. The update is relevant for Go developers using the Databricks SDK for data management tasks.
patch - Databricks Go SDK Releases sdkdatadatabricksengineer ·
Databricks SDK Go v0.143.0 Adds Accelerated Sync Field
Databricks SDK Go version 0.143.0 introduces a new `AcceleratedSync` field to `database.SyncedTableSpec` and `postgres.SyncedTableSyncedTableSpec`. This enhancement aims to improve synchronization performance for tables. The update is available to all users of the Go SDK for Databricks.
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 Python SDK Releases sdkaidatabricksengineer ·
Databricks SDK for Python v0.116.0: New APIs and Breaking Changes
Databricks SDK for Python v0.116.0 introduces new packages for AI Search and Bundle Deployments, along with numerous field additions across services like Catalog, ML, and Vector Search. This release also includes breaking changes with the removal of the `databricks.sdk.service.bundle` package and the associated workspace-level service. These updates primarily affect developers using the Python SDK to interact with Databricks services, offering expanded capabilities while requiring adjustments for bundled application deployments.
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 - Databricks Java SDK Releases sdkdatadatabricksengineer ·
Databricks SDK Java v0.118.0: Canonical Bearer token handling
Databricks SDK for Java version 0.118.0 introduces a bug fix for canonicalizing Bearer tokens in Authorization headers. This change ensures consistent handling of tokens, which is crucial for authentication and authorization in API interactions. The update includes an API change with a new `getCanonicalTokenType()` method for the `Token` class. This release is for developers using the Java SDK.
patch - Databricks Java SDK Releases sdkaidatabricksdeprecationengineer ·
Databricks SDK Java v0.117.0: Enhanced AI agent detection and pagination
Databricks SDK Java version 0.117.0 enhances AI agent detection by recognizing the AI_AGENT environment variable, improving user agent reporting for recognized AI tools. It also introduces explicit factory methods for pagination strategies, deprecating the direct constructor. Bug fixes address issues with paginators silently dropping results on empty pages. These updates benefit developers using the SDK for interacting with Databricks AI features and data listing operations.
patch - Databricks Python SDK Releases sdkaidatabricksengineer ·
Databricks SDK Python v0.115.0: Improved AI Agent Detection
The Databricks SDK for Python version 0.115.0 now respects the Vercel AI_AGENT environment variable for User-Agent detection. This change ensures that custom AI agent identifiers are passed through more accurately, allowing for better visibility into agent usage. The update benefits users employing custom AI agents with specific versioning.
feature - Databricks Java SDK Releases sdkdatadatabricksengineer ·
Databricks Java SDK v0.116.0: Optional Client ID in OAuth
Databricks Java SDK v0.116.0 allows the client ID to be optional in OAuth token acquisition. This fix prevents NullPointerExceptions for users authenticating via browser OAuth flows where the IdP JWT lacks a client ID, enabling account-wide token federation by omitting the parameter when it's absent. The change impacts developers using the Java SDK for OAuth authentication.
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 Python SDK Releases sdkdatabricksengineer ·
Databricks SDK for Python v0.114.0
Databricks SDK for Python v0.114.0 introduces new fields for deployment modes and collaboration platform connectivity. These updates enhance configuration options for Databricks deployments and integrations. The changes are available now and primarily affect developers working with the Databricks SDK.
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 Java SDK Releases sdkdatadatabricksengineer ·
Databricks SDK Java v0.114.0 Adds Token Management API and Workspace ID Changes
Databricks SDK Java v0.114.0 updates workspace addressing and introduces new token management capabilities. The change to workspace ID headers improves compatibility across different identifier formats. New fields and methods enhance control over job and pipeline deployments, as well as token creation and information retrieval, impacting engineers working with Databricks jobs, pipelines, and authentication.
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.
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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.