Releasesby GlyphDatabricks Runtime maintenance updates (08/04)
New maintenance updates are available for supported Databricks Runtime versions. These updates include bug fixes, security patches, and performance improvements. For details, see: Databricks Runtime 18 LTS Databricks Runtime 18.2 Databricks Runtime 18.1 Databricks Runtime 17.3 LTS Databricks Runtime 16.4 LTS Databricks Runtime 15.4 LTS Databricks Runtime...
Also shipped Aug 4, 2026Databricks in August 2026 →
Workspace sharing in Declarative Native Apps (Public Preview)
Workspace sharing is now available in public preview for Declarative Native Apps. Providers can share a whole directory of files and folders by declaring a workspace in the application package manifest. Consumers get a read-only workspace when they install the app, and can browse the folder structure and open the files.
Gateway Monitoring & A/B Testing (General availability)
Gateway Monitoring & A/B Testing is now generally available. Use gateway model monitors to track drift and performance for inference services behind a Snowflake Gateway, compare baseline and challenger services during live traffic splits, and evaluate results in Snowsight or with SQL. For more information, see Gateway monitoring & A/B testing .
Multi-party Approval (General availability)
Multi-party Approval (MPA) is now generally available. When a Multi-party Approval policy is attached to your account, MPA enforces a mandatory second-person (“four-eyes”) verification step for critical account operations. A Multi-party Approval policy defines which operations require approval and who can approve them.
AlloyDB now supports Best Matching 25 (BM25) indexes for full-text search in Preview
AlloyDB now supports Best Matching 25 (BM25) indexes for full-text search in Preview . You can use the pg_textsearch extension to create BM25 indexes and optimize probabilistic ranking of full-text search. This feature is supported on AlloyDB instances running PostgreSQL 17 or 18. For more information, see Create and manage a BM25 index .
Process-level sandboxing and auto-updates (Preview)
This release introduces process-level sandboxing, automatic update checks, and other improvements to the CodeMender CLI (Preview): Process-level sandboxing : To safeguard your workstation against unintended file modifications or unexpected tool side effects, you can now execute all agent-proposed tools (such as compiling code, running tests, or executing...
Looker Conversational Analytics engagement and token metrics in preview
Enhanced observability for Conversational Analytics, including engagement and estimated token usage, appears on the System Activity dashboard after an admin turns on the Agent Token usage preview setting.
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Search and replace text across files
You can now search and replace text across files in a Databricks Git folder or Declarative Automation Bundles project from the Search pane. See Search and replace across files .
Serverless compute access control is now generally available
Serverless compute access control is now generally available. Workspace admins can govern who runs serverless workloads through two built-in serverless compute objects: Default Interactive Compute (governs access to notebooks and Databricks Connect) and Default Automated Compute (governs access to jobs and Spark Declarative Pipelines on Lakeflow).
Organize your work with spaces
You can now use spaces to organize your work in the Databricks editor. Each space lets you focus on a specific folder or project while preserving your open tabs, so you can easily pick up where you left off. See Organize your work with spaces .
Filter updates for the Databricks Excel Add-in
The Databricks Excel Add-in now supports cascading filters and case-insensitive string matching. Additionally, the LIKE , NOT LIKE , IN , NOT IN , and ILIKE filters are no longer available in the filters list. See Filter imported data .
JAR tasks on serverless compute are now generally available
Package Scala or Java code as a JAR and run it as a task in a Lakeflow Job on serverless compute. Your JAR must match the Scala, Java Development Kit (JDK), and Databricks Connect versions of your serverless environment version. See Create and run JARs on serverless compute .
ai_search function (Beta)
The ai_search() SQL function retrieves information from one or more AI Search indexes configured as knowledge sources. Given a natural-language query, the function generates optimized search queries, retrieves and deduplicates results across sources, reranks them by relevance, and returns the most relevant documents.
Web terminal on serverless GPU compute (AI Runtime) is in Public Preview
The web terminal in notebooks connected to serverless GPU compute (AI Runtime) is now in Public Preview . Use it to run shell commands, monitor GPU usage with nvidia-smi , install libraries, and manage files directly on the compute. This requires serverless GPU environment version 5 or above. See Run shell commands in Databricks web terminal .
Databricks Runtime 19: August 10, 2026
New features and improvements collect_union aggregate function : SQL and the Scala and Python DataFrame APIs now support collect_union , which returns the distinct union of the elements in arrays within each group.