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 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 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 - 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.
breaking patch - Databricks Java SDK Releases sdkdatadatabricksengineer ·
Databricks SDK for Java v0.113.0 adds feature engineering APIs, includes breaking changes
Databricks SDK for Java version 0.113.0 introduces new methods for managing streaming objects within the feature engineering service. It also adds several new fields to existing Job and Pipeline task configurations. However, this release includes breaking changes, removing the `catalogId` and `syncedTableId` fields from specific Postgres-related status objects, which may require consumers to update their code.
breaking patch - Databricks Java SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Java v0.112.0: API additions and breaking changes
Databricks SDK for Java version 0.112.0 introduces several new methods and fields across various services, including workspace, IAM, jobs, and ML. Notably, it includes breaking changes related to required fields in bundle operations, tag types for marketplace listings, and pagination for cluster events. These updates primarily affect developers building applications and integrations with Databricks using the Java SDK.
breaking patch - Databricks Python SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Python v0.111.0: Bundle package, Lakeview revert, Postgres undelete
Databricks SDK for Python version 0.111.0 introduces a new bundle package and workspace-level services for Lakeview and Postgres, alongside several field additions across various modules. These changes primarily affect developers using the Python SDK for interacting with Databricks services. Notably, two breaking changes are included regarding tag handling for marketplace listings and pagination for cluster events.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.136.0: New features and breaking changes
Databricks SDK Go v0.136.0 introduces several new API methods and fields, enhancing functionality for Postgres workspace services and job management. It also includes breaking changes to the bundle operations and marketplace listing requests, requiring users to update their code for compatibility. This release primarily impacts developers using the Go SDK to interact with Databricks services.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.133.0 Introduces New IAM and Feature APIs
Databricks SDK Go version 0.133.0 adds significant new functionality for managing IAM assignments at both account and workspace levels, alongside enhancements for feature engineering and job task configurations. These updates benefit developers and architects working with Databricks for ML and data engineering, introducing new APIs and fields to support more complex use cases. Notably, several breaking changes are included, requiring developers to update their code when integrating these new features.
breaking patch - Databricks Python SDK Releases sdkdatadatabricksengineer ·
Databricks SDK for Python v0.109.0: New IAM, ML, and Serving features
Databricks SDK for Python version 0.109.0 introduces new methods for managing workspace assignments and several new fields across IAM, ML, and serving functionalities. Notably, it includes breaking changes to the `ListFeaturesRequest` and `list_features` method, impacting how features are requested and listed. This release is primarily for Python developers working with the Databricks platform, particularly those involved in account and workspace management, feature engineering, and model serving.
breaking patch - Databricks Java SDK Releases sdkdatabricksengineer ·
Databricks SDK for Java v0.108.0 includes breaking API changes
Databricks SDK for Java version 0.108.0 introduces several breaking changes, including modifications to Feature API fields and method signatures, and the removal of a resource name field. These changes primarily impact Java developers using the Databricks SDK for feature engineering and serving, requiring code updates for compatibility. New enum values for GPU workload types have also been added, alongside other feature enhancements.
breaking patch - Databricks Python SDK Releases sdkdatadatabricksengineer ·
Databricks SDK for Python v0.108.0 Updates
Databricks SDK for Python v0.108.0 introduces new fields for job task configuration and adds new connection types for catalog integrations. It also includes a breaking change by removing an unspecified resource name field. This release impacts developers building and managing Databricks workloads using the Python SDK.
breaking patch - Databricks Java SDK Releases sdkdatabricksengineer ·
Databricks SDK Java v0.107.0: New APIs, Breaking Changes, and CLI Fixes
Databricks SDK Java v0.107.0 introduces new APIs for workspace management, vector search, and job configurations, alongside several breaking changes in field requirements and removals. It also fixes a critical bug in the Databricks CLI profile fallback mechanism and enhances token refresh behavior. These updates primarily affect developers using the Java SDK for Databricks automation and integration.
breaking patch - Databricks Python SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Python v0.107.0 Enhances APIs and Fixes Auth
Databricks SDK for Python v0.107.0 introduces new API methods for supervisor agents and vector search endpoints, along with several new fields across various services like pipelines and settings. The release also includes a fix for the CLI's auth token command to ensure fresh tokens are used, addressing potential stale token issues. These changes are primarily for engineers and architects working with the Databricks platform.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.132.0: New Features and Breaking Changes
Databricks SDK Go version 0.132.0 introduces several new fields and enum values across various services, including pipelines, catalog, and vector search, enhancing connector options and metadata capabilities. Notably, it includes breaking changes by removing MinQps fields from vector search endpoint creation and patching, and modifying Description fields in supervisor agents and tools to be non-required. These updates primarily affect developers using the Go SDK to interact with Databricks services, requiring attention for any code relying on the removed or changed fields.
breaking patch - Databricks Java SDK Releases sdkinfradatabricks ·
Databricks SDK Java v0.106.0: New Features and Breaking Changes
Databricks SDK Java version 0.106.0 introduces new packages for disaster recovery and temporary volume credentials, alongside several API additions and field updates across various services. Some changes are backward-incompatible, notably the removal of the `connection` field from the `Tool` class and making the `description` field optional for `SupervisorAgent`. These updates primarily affect developers using the Java SDK to interact with Databricks services.
breaking patch - Databricks Python SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Python v0.106.0: New Features and Breaking Changes
Databricks SDK for Python version 0.106.0 introduces new workspace and account-level services, including temporary volume credentials, enhanced knowledge assistant capabilities, and disaster recovery features. It also adds numerous fields to existing services for data pipelines and Postgres management, alongside a breaking change in how connections and tools are handled in the supervisor agents service. This release affects developers using the Databricks SDK, particularly those interacting with workspace services or relying on the supervisor agents' connection fields.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.131.0: New APIs and Breaking Changes
Databricks SDK Go version 0.131.0 introduces several new API methods and fields across workspace, account, and compute services, including disaster recovery and knowledge assistants. Notably, there are breaking changes to the supervisor agents connection field. These updates primarily affect developers and architects working with the Databricks API via Go, requiring adjustments for specific supervisor agent interactions.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.130.0: Unified Host Support and API Additions
Databricks SDK Go version 0.130.0 introduces support for unified hosts, allowing a single configuration profile for account and workspace operations. This release also includes breaking changes, such as the removal of the experimental unified host detection field and the file-based OAuth token cache, which now defaults to an in-memory cache. Several new API endpoints and fields have been added, enhancing capabilities for managing volumes, knowledge assistants, apps, and pipeline connectors.
breaking patch - Databricks Java SDK Releases sdkinfraawsazuregcpdatabricksengineer ·
Databricks SDK Java v0.105.0: AI agent detection, breaking changes, new APIs
Databricks SDK Java v0.105.0 introduces automatic detection of AI coding agents in HTTP request headers, enhancing environment identification. It also includes breaking changes by removing the experimental unified host flag and several API method path updates. Several new APIs and fields have been added across services like secrets, supervisor agents, and postgres, with bug fixes for SPOG host compatibility.
breaking patch - Databricks Python SDK Releases sdkdatabricksengineer ·
Databricks SDK for Python v0.105.0 adds new APIs and breaking changes
Databricks SDK for Python version 0.105.0 introduces new packages and workspace-level services for supervisor agents and secrets, along with numerous field additions across various services. Several API methods have undergone breaking changes, including modifications to their paths, requiring users to update their code. These updates are primarily relevant to software engineers and architects developing integrations with Databricks.
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.