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 blogaidatabricksgaengineerretail ·
Databricks AI Search adds high-QPS scaling
Databricks AI Search now supports scaling endpoints to thousands of queries per second (QPS) with a single configuration parameter, eliminating the need for manual replica management or load balancing. This feature is crucial for real-time applications like search bars, recommendation systems, and entity resolution that experience high traffic volumes. It's generally available today for all users, simplifying the transition from prototype to production.
feature announcement - Databricks Blog blogaidatabricksgaengineer ·
AI Literacy Framework for Education and Workforce
Databricks introduces a comprehensive AI literacy framework designed to equip individuals with functional, critical, and ethical skills for responsible AI use. The framework, organized around understanding, evaluating, and using AI, aims to guide higher education institutions and organizations in curriculum development and workforce training. This initiative addresses the growing demand for AI proficiency as AI tools become integral to daily work, projecting significant shifts in workplace skills.
announcement - Databricks Blog blogdatabricksgaengineerhealthcare ·
Imperial College London Accelerates Dementia Research with Databricks Platform
Imperial College London modernized its dementia research platform by integrating IoT, clinical, and research data using Databricks. This new architecture separates workloads, enhances data access via Unity Catalog, and empowers non-technical users to explore patient insights. The platform significantly reduced data integration timelines from six months to one month, accelerating model development and improving dementia care.
announcement feature - 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 - 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 sdkazuregcpdatabricksgadeprecationengineer ·
Databricks SDK for Go v0.127.0 Release
Databricks SDK for Go v0.127.0 introduces several new features, including host metadata customization and lazy iteration with limits. It also contains numerous bug fixes, particularly around token acquisition and caching for various credential providers. Breaking changes include raising the minimum Go version and removing a field from the Postgres SyncedTableSpec. These updates affect developers using the Go SDK for interacting with Databricks services.
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.