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 blogaidatabricksmedia ·
Databricks Accelerates Agentic Media Buying with New Reference Implementation
Databricks has released a reference implementation and self-deploy accelerator for agentic media buying, enabling autonomous buyer and seller agents to transact business on its platform. This solution addresses the critical need for governed data, transactional state, identity, hosted models, and end-to-end observability, which are often bottlenecks in agent-based projects. The accelerator aims to provide a working blueprint for teams to deploy in their own workspaces, streamlining the media buying process which traditionally involves significant manual coordination. Buyer and seller organizations can adapt these agents to their environments and transact with partners over open standards.
feature announcement - Databricks Blog blogdataanalyticsdatabricksengineermedia ·
NBCUniversal Migrates to Databricks Lakehouse for Scalable Analytics
NBCUniversal successfully migrated its data infrastructure to the Databricks Lakehouse Platform, achieving a 30% cost reduction by switching to dedicated job compute. This move enables independent scaling of data pipelines, faster job completion, and meets Service Level Agreements. The migration impacts data analysts, engineers, and scientists by providing a unified platform for advanced ML model development and real-time analytics, with a phased, partner-led implementation by EXL minimizing disruption.
feature patch announcement - Databricks Python SDK Releases sdkdatadatabricksengineer ·
Databricks SDK for Python v0.123.0: API changes and breaking updates
Databricks SDK for Python version 0.123.0 introduces several new workspace-level services and API fields, including AI Gateway and expanded telemetry configuration. Notably, breaking changes affect the bundle deployments service with modified method signatures and removed fields, impacting how developers manage deployments. This release primarily affects users of the Databricks SDK for Python, particularly those working with bundle deployments or integrating AI Gateway.
breaking patch - Databricks Go SDK Releases sdkaidatabricksengineer ·
Databricks Go SDK v0.167.0 Adds Cloud Provider Auth Fields
The Databricks Go SDK has been updated to version 0.167.0, introducing new fields for cloud provider authentication within the catalog service. These additions allow for more direct configuration of authentication methods with services like Amazon Bedrock and Azure OpenAI, impacting engineers and architects working with Databricks integrations. The update enhances flexibility for securing access to AI model providers.
patch - Databricks Java SDK Releases sdkaidatabricksengineer ·
Databricks SDK Java v0.138.0 Adds Model Provider Config Fields
Version 0.138.0 of the Databricks SDK for Java introduces new fields to model provider configurations, enhancing integration capabilities. These changes allow for more direct configuration of specific cloud provider details, impacting developers using the SDK for MLOps and AI model deployment. The updates are now available in the latest SDK release.
patch - Databricks Blog blogdatadatabricksengineer ·
Databricks Genie Code Beta: Agentic Converter for SQL Dialect Migration
Databricks has launched the Agentic Converter in Genie Code as a beta feature, utilizing AI agents to automate the conversion of proprietary SQL dialects (T-SQL, Snowflake, Redshift, Oracle, BigQuery, Teradata) to open ANSI SQL. This aims to simplify and accelerate legacy data warehouse migrations to the Databricks Lakehouse by handling code analysis, iterative conversion, and syntax validation. The tool introduces migration projects for tracking progress and lineage, alongside custom skill creation for tailored conversions, making data warehouse migration a configurable and monitorable process.
feature announcement - Databricks Blog blogaidatabrickspreviewengineer ·
Databricks Agentic Code Converter transitions proprietary SQL to ANSI SQL in Beta
Databricks Genie Code now includes an agentic code converter, available in Beta, designed to automate the migration of proprietary SQL dialects to open ANSI SQL. This tool uses parallel agents for iterative conversion and validation, aiming to simplify legacy data warehouse migrations for Databricks users. The converter supports T-SQL, Snowflake, Redshift, Oracle, BigQuery, and Teradata, with features like migration project management, code complexity analysis, and lineage tracking to guide the process.
feature announcement - Databricks Blog blogaidatabricksengineerfinance ·
Databricks Genie AI Coworker for Telecom Finance
Databricks introduces Genie, an AI coworker designed for telecom finance teams to combat revenue leakage by providing accurate, context-aware answers to complex financial questions. By leveraging an ontology that learns the business, Genie helps identify and prevent unbilled services, fraud, partner settlement errors, and customer churn in real-time. This allows finance professionals to move beyond manual reconciliation and act proactively to retain revenue, with early adopters like Lumen Technologies seeing significant time savings. Genie is now available for finance teams to improve revenue assurance and operational efficiency.
feature announcement - Databricks Blog blogaidatabricksengineerhealthcare ·
Databricks Genie: AI Coworker for Healthcare Finance
Databricks has introduced Genie, an AI-powered coworker designed to address the challenges faced by healthcare finance teams operating on fragmented and outdated data. Genie leverages an ontology to provide contextually correct financial insights, enabling faster and more accurate decision-making. This feature aims to help finance professionals understand cost vs. reimbursement, identify revenue leakage from denials, and track trapped cash in receivables, ultimately protecting the organization's margin.
feature announcement - Databricks Blog blogaidatabricksengineerfinance ·
Databricks Genie: AI Coworker for Manufacturing Finance
Databricks has introduced Genie, an AI coworker designed to help manufacturing finance teams manage capital and protect margins. Genie addresses complexities introduced by AI agents by providing context and control through an evolving business ontology. It answers key questions about trapped cash in inventory, aging receivables, and underperforming assets, offering traceable and actionable insights for finance professionals.
feature announcement - Databricks Blog blogaidatabricksengineerfinanceenergy ·
Databricks Genie: AI Coworker for Energy Finance
Databricks has launched Genie, a new AI coworker designed to help energy finance professionals navigate market volatility and protect margins. Genie utilizes an ontology to provide context-aware, traceable answers to critical financial questions, distinguishing it from standard BI tools. It aims to help finance teams manage revenue risk and capital allocation for AI-driven power demand, offering a governed and continuously learning system for critical decision-making.
feature announcement - Databricks Blog blogdatadatabricksengineer ·
Databricks Agents for Real-Time Production Line Decisions
Databricks introduces AI agents for production lines, enabling immediate, data-driven decisions to optimize operations. These agents ingest real-time streaming data from OT, MES, ERP, and LIMS into the Databricks Data Intelligence Platform. This integration allows for faster root cause analysis and recommendations, improving Overall Equipment Effectiveness (OEE) and reducing costly downtime for CPG companies and other manufacturers. The system provides in-shift answers rather than next-day reports, with recommendations drafted as work orders for human approval.
feature announcement - Databricks Blog bloggovernancedatabricksengineerfinancegovernment ·
Databricks enables real-time fraud prevention for government benefits
Databricks is enhancing fraud prevention for government benefit programs by leveraging its data and AI platform. This approach aims to shift from a reactive 'pay and chase' model to real-time detection, significantly reducing billions lost annually to fraud. The platform facilitates cross-agency data sharing and sophisticated AI-driven risk scoring for entities like federal departments that already utilize Databricks.
feature announcement - Databricks Blog blogaidatabricksengineerfinancemedia ·
Databricks Genie: AI Coworker for Media Finance
Databricks has introduced Genie, a data-smart AI coworker designed to help media finance teams manage audience value and protect margins. Genie leverages an ontology to provide accurate, context-aware answers to complex financial questions, improving decision-making in areas like subscription pricing and advertising yield. This tool aims to bridge the gap between raw data and actionable insights for finance leaders, marketing, and operations teams within media companies.
feature announcement - Terraform Databricks Provider Releases terraforminfradatabricksengineerdatabricks-unity-catalog ·
Databricks Terraform Provider v1.123.0: Improved Plan Validation, Delta Sharing, MLflow, and Bug Fixes
Databricks Terraform provider version 1.123.0 shifts workspace ID validation from plan to apply, resolving false-positive plan failures for certain configurations. It also introduces a data source for Delta Sharing recipients and enhances MLflow experiment tracing with Unity Catalog integration. Several bug fixes address issues with view column comments and access control rule set drift detection, impacting users managing Databricks resources via Terraform.
patch - Databricks Java SDK Releases sdkaidatabricksengineer ·
Databricks SDK Java v0.137.0 adds AI Gateway and deployment fields
Databricks SDK Java version 0.137.0 introduces new features and enhancements to the bundle deployment service and adds a new AI Gateway service. These updates provide expanded capabilities for managing AI services and improve the granularity of information available for deployment tracking. The release is intended for developers and architects working with Databricks integrations.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Go v0.166.0 Enhances Workspace Services
Databricks has released version 0.166.0 of its Go SDK, introducing new workspace-level services and enhancing existing ones. Key additions include an AiGateway service and an UpdateOperation method for BundleDeployments, along with expanded fields for deployment and operation details. These changes provide developers with more granular control and visibility over workspace resources, particularly for deployment management.
patch - 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 blogaidatabricksengineer ·
Databricks uses Unity AI Gateway for internal AI coding agent spend control
Databricks has implemented internal controls for its AI coding agent spend by routing all traffic through Unity AI Gateway, enforcing unified budgets and policies. This system separates daily limits for runaway spend protection from higher monthly limits for extraordinary use, balancing innovation with cost control. It allows engineers to self-service budget increases for normal usage, reducing bottlenecks and enabling faster adoption of AI tools.
announcement feature - Databricks Java SDK Releases sdkdatabricksengineer ·
Databricks SDK Java v0.136.0 Updates
Databricks SDK Java has been updated to version 0.136.0, introducing new API capabilities. These changes include the addition of a method for patching telemetry configurations and new fields for schema specifications and SQL alerts. The updates primarily affect developers using the Java SDK to interact with Databricks services like serving endpoints and pipelines.
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.