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 bloginfradatabricksengineer ·
Databricks Builds Self-Serve Infrastructure Vending Machine for Field Engineering
Databricks has developed the Field Engineering Vending Machine (FEVM), a Databricks App that provisions isolated, governed, and use-case-specific cloud resources on demand. This addresses infrastructure challenges faced by their growing field engineering organization of over 7,000 people, enabling faster development and agent-first framework adoption. The system uses Terraform for provisioning across AWS, Azure, and GCP, with transparency and audibility built-in.
feature announcement - Databricks Blog blogaidatabricksengineer ·
Databricks Genie Code Agent Outperforms General Agents in Accuracy and Cost
Databricks evaluated its data agent, Genie Code, against three general coding agents on over 400 real-world tasks. Genie Code proved to be the most accurate and cost-efficient, delivering correct answers at less than half the cost of other agents. This performance stems from its deep semantic understanding of enterprise context and specialized capabilities, allowing it to navigate complex data workspaces more effectively than general-purpose agents. The evaluation included a wide spectrum of tasks such as data discovery, code creation, debugging, and data lookups, highlighting Genie Code's advantages for full-spectrum data work.
announcement feature - Databricks Blog blogawsdatabricksengineer ·
Databricks Simplifies S3 Data Connection with Delegated IAM Permissions
Databricks has introduced a streamlined, automated flow for connecting Amazon S3 buckets to Unity Catalog, reducing manual configuration from days to minutes. This new method uses AWS IAM temporary delegation, eliminating the need for complex IAM policies and CloudFormation templates, and directly benefiting users by simplifying a foundational step for data ingestion, pipelines, and analytics. The process is now a few clicks within the Databricks workspace, automatically provisioning necessary storage credentials and external locations with least-privilege permissions. Users lacking sufficient AWS access can request it from their administrator directly within the flow, and the authorization automatically expires after provisioning, enhancing security.
feature - 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 - Databricks Blog blogaidatabricksengineer ·
Databricks simplifies AI agent orchestration with Lakebase Postgres
CliftonLarsonAllen (CLA) collaborated with Databricks to build a fully Databricks-native solution for agentic auditing and document processing. The solution leverages Lakebase Postgres as an orchestration backbone, eliminating the need for external infrastructure like message brokers or schedulers. This approach addresses challenges such as unpredictable task latency, rate-limiting, workload prioritization, cost attribution, and real-time visibility for long-running agentic tasks.
feature announcement - Databricks Blog blogdataaidatabricksengineer ·
Databricks: Bridging the Gap Between Data and Marketing Campaigns
This article explains how the 'composable canvas' architecture, powered by Databricks, closes the gap between first-party data and actual marketing campaign execution. By unifying data foundations and enabling AI agents, it eliminates integration bottlenecks and speeds up campaign activation. This is crucial for marketing teams struggling with siloed tools and delayed data activation, allowing them to leverage rich customer signals for personalized campaigns.
announcement feature - Databricks Blog blogdatagovernancedatabricksengineer ·
Dow Builds Carbon Footprint Ledger on Databricks for Sustainability
Dow has implemented a Carbon Footprint Ledger (CFL) on the Databricks Data Intelligence Platform to calculate cradle-to-gate Product Carbon Footprints (PCFs) for its entire product portfolio. This initiative significantly reduces processing time from weeks to a fraction of that by leveraging Apache Spark, Delta Lake, Unity Catalog, and MLflow, enabling faster optimization and verifiable certification of low-carbon products. The system is designed for third-party assurance against ISO 14067 and the GHG Protocol Product Standard, benefiting both Dow's sustainability goals and its customers' Scope 3 emission reduction efforts.
announcement feature - Databricks Blog blogdatadatabrickspreviewdatabricks-unity-catalog ·
Databricks Previews Unity Catalog Discover and Domains for Data Marketplace
Databricks has launched a Public Preview of its internal data and AI marketplace, "Discover," and a business context layer called "Domains," both powered by Unity Catalog. These features aim to help users and AI agents find trusted, relevant data and AI assets more easily by organizing them around business structures. This is particularly beneficial as data estates grow and AI agents require contextual understanding for reliable results.
feature announcement - 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 - Databricks Blog blogdatadatabricksengineerarchitect ·
Branching Lakebase databases like code for CI/CD
Glaspoort implemented a CI/CD pattern for their Databricks Lakebase, treating database changes with the same rigor as application code. This involves branching every environment directly from production and using ephemeral per-PR databases, with migrations as the single source of truth. This approach aims to avoid the common "reset-from-parent trap" that causes environments to drift from production and necessitates costly rebuilds. The pattern allows for faster, more reliable database updates in production environments.
feature announcement - Databricks Blog blogaidatabricksengineer ·
Databricks combines vector search and AI Classify for efficient large-scale document classification
Databricks has introduced a new method for classifying documents against taxonomies with over 100,000 labels, addressing limitations of existing approaches like regex and direct LLM calls which struggle with cost, maintenance, and context windows. The solution pairs vector search with the Databricks AI Classify function, retrieving a shortlist of candidate labels before AI Classify makes the final selection. This hybrid approach has demonstrated higher accuracy at a significantly lower cost compared to using frontier models alone across multiple benchmarks, benefiting thousands of Databricks customers dealing with use cases like biomedical entity linking and vendor normalization.
feature announcement - Databricks Java SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Java v0.131.0 adds fields, includes breaking API changes
Databricks SDK Java version 0.131.0 introduces new fields across several services, including ML, Jobs, Networking, and Workspace. This release also contains breaking changes affecting IAM v2 client methods and the TimeWindow object in ML, requiring consumers to update their code. These updates are now generally available.
breaking patch - Databricks Blog blogaidatabricksengineerfinance ·
Databricks Genie One powers AI-driven finance operations
Databricks has introduced Genie One, an AI coworker designed to help finance teams in tech and AI-native companies manage complex unit economics. It addresses the challenge of rapidly changing business metrics by grounding answers in a constantly updated ontology, providing real-time insights into gross margin, consumption revenue, and compute spend. This allows finance professionals to proactively protect growth economics by identifying risks and opportunities before they impact the business.
feature announcement - Databricks Blog blogaigovernancedatabricksengineer ·
Databricks Unity AI Gateway adds Model Provider Services
Databricks introduced Model Provider Services (MPS) in Unity AI Gateway, allowing organizations to securely access and govern external AI models like Meta's Muse Spark 1.1. This feature centralizes API key management, enforces access controls via Unity Catalog, and provides end-to-end observability for usage and spend. MPS aims to simplify the adoption of new AI models by consolidating governance and security across different providers.
feature announcement - Databricks Blog blogdataaidatabricksengineer ·
Databricks Coach's Corner: Soccer App Leverages Full Platform
Databricks has launched Coach's Corner, a soccer coaching application that transforms 51 million rows of match data into a real-time 2D/3D tactical analysis tool. This end-to-end solution showcases the Databricks platform's capabilities from data ingestion via Lakeflow to AI scouting with Genie and Vector Search, all governed by Unity Catalog. The app is designed for coaches to make split-second decisions by providing low-latency data access for replays and optimized query paths for complex analytics, demonstrating a unified approach to data and AI on the platform.
feature announcement - Databricks Python SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Python v0.121.0: API updates and breaking changes
Databricks SDK for Python version 0.121.0 introduces new fields and methods across various services, including workspace grants, disaster recovery, and machine learning aggregations. Notably, several breaking changes are implemented, such as making the 'role' field required for PostgreSQL database specs and removing fields related to secret browsing and distinct count aggregations. The release also includes improved documentation for authentication types, benefiting developers using the SDK.
breaking patch - Databricks Blog blogaidatabricksengineer ·
Databricks Introduces Unified Context for Enterprise AI
Databricks unveiled Genie One and Genie Ontology to address scattered business context, a key limitation for AI assistants in decision-making. Genie One acts as an AI coworker, leveraging unified context to provide business-term answers grounded in trusted data and enable actions within existing tools. Genie Ontology serves as the central context layer, mapping business operations to help AI understand and follow key concepts across systems, making AI-driven decisions more reliable and efficient for businesses.
feature announcement
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.