Releasesby GlyphDeepSeek V4 Flash (0731) is retired
Databricks retired the DeepSeek V4 Flash (0731) model. Users are advised to migrate to DeepSeek V4.1 Flash (1017).
Databricks Data Intelligence Platform Release notes from Databricks
118 releases · 4 this month
Simba JDBC Driver (Legacy) 2.8.7 is available
Simba JDBC Driver (Legacy) 2.8.7 updates jackson-core , jackson-databind , and jackson-datatype-jsr310 to 2.21.8. Download it from the JDBC drivers archive under All JDBC Driver Versions (Simba) .
DeepSeek V4 Pro (0813) is retired
DeepSeek V4 Pro (0813) has been retired. DeepSeek V4.1 Flash (1017) is the recommended replacement.
Data quality monitoring anomaly detection is now generally available
Anomaly detection for data quality monitoring is now generally available. Enable it at the schema level to monitor the freshness and completeness of every table in the schema, based on historical data patterns. Results for all monitored tables are stored in the system.data_quality_monitoring.table_results system table, which is also now generally available.
Account-level security features are now available by default at GA
Account-level security features, including network connectivity and encryption controls, are now available by default upon general availability. Admins no longer need to manually enable these features on the Previews page.
DataFrame caching on serverless compute is now in Public Preview
Databricks now supports DataFrame caching on serverless compute via df.cache() or df.persist(), allowing users to reuse results within a session.
Shared Serverless (Beta)
Shared Serverless allows notebooks and files within the same bundle to share serverless compute resources and environment configurations defined in a pyproject.toml file.
DeepSeek V4.1 Flash is scheduled for retirement
DeepSeek V4.1 Flash will be retired on November 19, 2026. DeepSeek V4.1 Flash (1017) is the recommended replacement. See Deprecated and retired models for migration guidance.
ADBC driver for Power BI is now generally available
The Arrow Database Connectivity (ADBC) driver for the Databricks connector for Power BI is now generally available. ADBC is the default driver for new connections in Power BI Desktop and the Power BI service. See Configure ADBC or ODBC driver for Power BI .
AI Runtime will soon be available by default for workspaces with the compliance security profile enabled
AI Runtime is scheduled to become generally available on October 15, 2026, on AWS and Azure for workspaces without the compliance security profile enabled. AI Runtime will be available by default for eligible workspaces with the compliance security profile enabled in mid November. Availability depends on the supported compliance standards and regions.
Private connectivity from serverless compute to AWS-managed resources is now generally available
AWS Private Link from Databricks serverless compute to AWS-managed resources, such as S3 buckets, previously in Public Preview, is now generally available. Your data traffic remains entirely within the AWS network and never traverses the public internet. See Configure private connectivity to AWS-managed resources .
Context-based ingress policies for inbound private connectivity are now generally available
Context-based ingress policies for inbound Private Link are now generally available. Control which registered VPC endpoints can reach your workspaces, and combine endpoint rules with identity and request type conditions in the same policy.
DeepSeek V4 Flash (0731) is scheduled for retirement
DeepSeek V4 Flash (0731) will be retired on November 5, 2026. DeepSeek V4.1 Flash is the recommended replacement. See Deprecated and retired models for migration guidance.
OAuth custom identity claims for service principal tokens will soon be available
Applications will be able to attach a custom identity claim to the OAuth tokens they request for a service principal, by adding the custom_claim parameter to a token request that uses the client_credentials or urn:ietf:params:oauth:grant-type:token-exchange grant type.
Customer-managed keys for query history are now generally available
You can now use a customer-managed key on the system catalog to decrypt statement_text and error_message in the query history system table. See Reading encrypted fields .
Schedule automatic data refresh in the Databricks Excel Add-in (Public Preview)
You can now schedule automatic refreshes of Databricks data imported into Microsoft Excel. Choose an interval or calendar schedule and the SQL warehouse that runs each refresh, then review recent runs from the Databricks Excel Add-in. See Schedule automatic data refresh in the Databricks Excel Add-in .
Control spreadsheet writeback with a workspace admin setting
Excel and Google Sheets writeback now requires a workspace admin to enable the Allow spreadsheet writeback security setting. See Write data back to Databricks using the Databricks Excel Add-in and Write data back to Databricks from Google Sheets .
ai_parse_document quality improvements: signature detection and layout prediction
ai_parse_document now detects signature regions in documents and identifies document layouts more accurately. See ai_parse_document function .
Thinking Machine Labs Inkling is scheduled for retirement
Thinking Machine Labs Inkling will be retired on October 30, 2026. GLM 5.3 and Kimi K3 are the recommended replacements. See Deprecated and retired models for migration guidance.
DeepSeek V4 Pro (0813) is scheduled for retirement
DeepSeek V4 Pro (0813) will be retired on October 30, 2026. DeepSeek V4.1 Flash is the recommended replacement. See Deprecated and retired models for migration guidance.
Bundled BigQuery JDBC driver removal in Databricks Runtime 20
Starting with Databricks Runtime 20, Databricks Runtime no longer includes the bundled BigQuery JDBC driver, while Databricks Runtime 19 and earlier continue to include it. Classic compute workloads that use Spark JDBC with a jdbc:bigquery: URL fail with a driver-not-found error unless a BigQuery JDBC driver is installed.
The query history system table is now generally available
The system.query.history system table is now generally available. Use it to access account-wide records for queries run on SQL warehouses or serverless compute, including execution status, duration metrics, and query source. See Query history system table reference .
Base environments are now supported on classic compute (Beta)
You can now use base environments to manage Python dependencies on classic compute. You can use Databricks-provided environments or custom workspace-level environments. See Manage dependencies using environments .
Anthropic models will be removed from AWS GovCloud IL5 workspaces
On September 19, 2026, Anthropic models will be removed from Databricks on AWS GovCloud and AWS GovCloud DoD workspaces that have the DoD Impact Level 5 (IL5) compliance standard selected. After this date, IL5 workspaces can't create or use endpoints that serve Anthropic models.
Automatic change data feed will soon be available in all supported regions
Automatic change data feed (Auto CDF) is rolling out to workspaces over the next month and will be available in all supported regions by the end of October 2026. Auto CDF computes row-level changes at query time using row tracking, so you don't need to enable change data feed on each Delta Lake or Apache Iceberg v3 table.
The counter_diff SQL window function is now available
The counter_diff window function calculates differences between consecutive cumulative counter values and handles counter resets, for time-series analysis of counter data. It is available in Databricks SQL and Databricks Runtime 19 and above. See counter_diff analytic window function .
The Databricks Excel Add-in is now generally available
The Databricks Excel Add-in is now generally available. Connect Microsoft Excel to your Databricks workspace to browse and import governed Unity Catalog tables and views, run SQL queries, build pivot tables, use custom functions, and write data back to Unity Catalog.
Configurable retention for system tables is in Beta
Account admins can now set an account-wide retention period from 30 to 3,650 days for supported system tables. See Configure system table data retention .
See which chunks support each ai_search answer (Beta)
You can now turn on the generate_citations option in the ai_search function to see which retrieved chunks the model used to support each answer it generates. ai_search function
Environment version 6 is now available
You can now select environment version 6 as your base environment for serverless and standard classic compute. See Environment version 6 .
Git Folder Serverless is in Beta
You can now use Git Folder Serverless to share serverless compute and a pyproject.toml -managed environment across notebooks and files in a Git folder. See Git Folder Serverless .
Automatic change data feed is now generally available
Automatic change data feed (Auto CDF) computes row-level changes at query time using row tracking, without requiring you to manually enable change data feed on each Delta Lake or Apache Iceberg v3 table. Auto CDF removes write-time overhead and makes MERGE and UPDATE operations about 15% faster on tables that you query for changes.
ai_transcribe function (Beta)
The ai_transcribe() SQL function transcribes an audio file into text. It returns the transcript as time-stamped segments, and labels each segment with a speaker when speaker diarization is enabled for your workspace. The output is a VARIANT value, so you can chain it into other AI Functions. This feature is in Beta . See ai_transcribe function .
Query text is now masked by default in system tables and APIs
Because SQL statements can contain sensitive information, Databricks now masks query text in the following places: statement_text in system.query.history returns . query_text in the Query History API and the List Queries API returns . Keys in request_params in system.access.audit that contain SQL definitions are omitted.
ai_prep_search supports plain text and markdown input (Beta)
The ai_prep_search() SQL function now accepts plain text and markdown STRING content in addition to the structured VARIANT output of ai_parse_document . You can now chunk and prepare text that you already have as a string for AI Search indexing and retrieval-augmented generation (RAG) pipelines, without first running it through document parsing.
Private network gateway is in Private Preview
Private network gateway is in Private Preview . A private network gateway connects Databricks serverless compute to resources in your VPC, on-premises systems, and the internet through a single managed gateway, reusing your existing network connectivity configuration (NCC).
Upcoming end of life for the Supervisor API
The Supervisor API (Beta) reaches end of life on September 30, 2026. After that date, the API is no longer available. Databricks recommends migrating to custom agents on Databricks Apps . See Supervisor API (Beta) (deprecated) .
Write data back to Databricks from Google Sheets
The Databricks Connector for Google Sheets now lets you write data from Google Sheets back to a Unity Catalog table. You can create a new table or overwrite an existing table without leaving Google Sheets. See Write data back to Databricks from Google Sheets .
ai_extract precision mode is now generally available
You can now use ai_extract precision mode for advanced extraction workloads, including multi-page documents, schemas with 50 or more fields, many extracted items per document, and complex conditional field logic. See ai_extract function .
Manage project environments with %uv commands
You can now use %uv init , %uv add , and %uv sync in serverless notebooks running environment version 5 or above to create a Python project, add dependencies, and sync its environment. See Create reproducible project environments with %uv .
Cross-workspace access for serverless (Beta)
You can now control serverless network traffic between Databricks workspaces. Account admins use cross-workspace access to set which source workspaces can reach a workspace (ingress) and which destination workspaces a workspace's serverless workloads can send traffic to (egress).
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.
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.
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 .
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 .
Databricks 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...
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).
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 .
Automatic upgrades begin rolling out row tracking and Checkpoint V2 to existing tables
Automatic upgrades begin rolling out row tracking and Checkpoint V2 to existing Unity Catalog managed tables, not just new tables. This rollout is gradual, so these features will be available to different customers at different times.
Git CLI commands in Git folders are now in Public Preview
Git CLI commands in Git folders are now in Public Preview . Git folders that you create from the UI automatically get Git CLI access when your workspace is eligible, so you can run standard Git commands such as git stash , interactive rebase, pre-commit hooks, Git submodules, and Large File Storage (LFS) directly from a Databricks terminal.
Databricks Runtime 18 and Databricks Runtime 18 for Machine Learning have transitioned to LTS
With the general availability of Databricks Runtime 19, Databricks Runtime 18 and Databricks Runtime 18 for Machine Learning have transitioned to long-term support (LTS). LTS versions receive three years of stability and security fixes. For release notes, see Databricks Runtime 18 LTS and Databricks Runtime 18 LTS for Machine Learning .
Email notifications for expiring service principal tokens are now generally available
Databricks now automatically sends an email notification when a service principal token is set to expire within seven days. Because service principals don't have their own mailboxes, Databricks sends these notifications to workspace admins.
Context-based ingress control for workspaces public access is now generally available
Context-based ingress control for workspaces public access is now generally available. Control who can reach your workspace endpoints using allow and deny rules that allow you to combine identities, network sources, and request types. See Context-based ingress control .
Agentic code converter is in Beta
The agentic code converter is in Beta . Use it to convert legacy SQL dialects, such as T-SQL, Snowflake, Redshift, Oracle, BigQuery, and Teradata, to ANSI SQL in migration projects in your workspace.
AI Search High QPS is now generally available
AI Search High QPS is now generally available for standard endpoints. Set a target QPS on standard AI Search endpoints to power high-throughput, real-time workloads like search bars, recommendation systems, and entity matching. High QPS is enabled by default, but existing endpoints are not affected.
Allowlist partner platform IPs in context-based ingress control (Beta)
Context-based ingress control now supports Partner Platforms as a network source. Select a partner platform to allowlist the IPs that third-party apps use to connect to Databricks, including Power BI, Tableau Cloud, and dbt platform. Databricks manages and updates these IP lists automatically. See Network sources .
View warehouse activity details (General Availability)
The Activity details toggle in the SQL warehouse monitoring UI is now generally available. View color-coded annotations on the Running clusters chart that explain why a warehouse remains active, including query activity, fetching queries, open sessions, and idle states.
Object metadata column is now in Public Preview
The _object_metadata column is now in Public Preview. The _object_metadata column is a hidden metadata column that exposes object-level properties for objects in cloud storage, including MIME type, ETag, user-defined key-value metadata, system-defined metadata, and object tags. It is available starting from Databricks Runtime 18.1.
July 6, 2026
This serverless compute release includes updates from Databricks Runtime 18 . New features Spark Declarative Pipelines on Lakeflow streaming query ID : Spark Declarative Pipelines on Lakeflow can now set the streaming query ID on demand.
Okta support for automatic identity management is now generally available
Okta support for automatic identity management is now generally available. Automatic identity management lets you sync users and groups from Okta into Databricks without SCIM provisioning.
About and activity
Workspaces, compute, notebooks and platform administration.
Other Databricks products: Agent Bricks and Mosaic AI, AI/BI and Genie, Databricks Apps, Databricks SQL, Delta Lake, Lakebase, Lakeflow, MLflow, Unity Catalog
Releases per month
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Official release-notes pages 14
| Release-notes page | Site | Feed |
|---|---|---|
| AI/BI (dashboards, Genie) docs.databricks.com | docs.databricks.com | None |
| Databricks CLI releases github.com | github.com | RSS |
| Databricks Connect docs.databricks.com | docs.databricks.com | None |
| Databricks Runtime docs.databricks.com | docs.databricks.com | None |
| Declarative Automation Bundles docs.databricks.com | docs.databricks.com | None |
| Developer tools (CLI, SDK, Terraform) docs.databricks.com | docs.databricks.com | None |
| Feature Store docs.databricks.com | docs.databricks.com | None |
| Platform release notes (AWS) docs.databricks.com | docs.databricks.com | RSS |
| Python SDK releases github.com | github.com | RSS |
| Serverless compute docs.databricks.com | docs.databricks.com | None |
| Serverless environment versions docs.databricks.com | docs.databricks.com | None |
| Terraform provider releases github.com | github.com | RSS |
| Unity AI Gateway docs.databricks.com | docs.databricks.com | None |
| What's coming docs.databricks.com | docs.databricks.com | None |