Databricks Release Notes

You can now set the effort level for Genie Code to balance response quality and cost. Auto (default) gives you the highest quality responses. For simpler tasks, select Low to use a faster, lower-cost model. See Select a level of effort.

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.

In late September 2026, user authorization for Databricks Apps will be automatically enabled for workspaces with the compliance security profile enabled. User authorization allows apps to act with the identity of the app user, so apps can access resources on the user's behalf while enforcing the user's existing permissions.

See User authorization.

The downstream_impact column in the data quality monitoring results system table is being deprecated.

Deprecation begins September 7, 2026, and rolls out gradually across regions over the following week. Until the rollout reaches your workspace, you might still be able to query downstream_impact. After deprecation completes, the column is no longer populated.

For the affected column, see Data quality monitoring results system table reference and Review anomaly detection logged results.

The root_cause_analysis column in the data quality monitoring results system table is being deprecated.

Deprecation begins August 18, 2026, and rolls out gradually across regions over the following several days. Until the rollout reaches your workspace, you might still be able to query root_cause_analysis. After deprecation completes, the column is no longer populated.

For the affected column, see Data quality monitoring results system table reference and Review anomaly detection logged results.

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.

Restore the Python variables and Spark session from a serverless compute job run into a new interactive notebook, so you can debug a failure or explore results without rerunning the job. Databricks automatically captures a state snapshot when an eligible run fails, runs 30 minutes or longer, or is cancelled, and keeps it for 7 days after the run completes. This feature is in Beta. See Session restore for serverless jobs.

Identity attributes are in Beta. You can now write Unity Catalog ABAC column mask policy conditions that target users by attributes synced from your identity provider, such as department or country, in addition to group membership. The has_identity_attribute_value and has_identity_attribute_tag_match functions are supported in the WHEN clause of column mask policies.

See identity attributes.

Programmatic management of Lakebase Postgres is now generally available through the REST API, Databricks CLI, and Databricks SDKs (Python, Java, Go). These interfaces support operations for projects, branches, endpoints, databases, roles, credentials, synced tables, and catalogs. See Lakebase API guide.

DeepSeek V4 Pro (0813) is now available on Unity Gateway for complex reasoning and agentic coding workflows. Access it through the same governed API as other models, with centralized permissions, guardrails, spend controls, and observability, and switch models without changing application code.

To query the model and see supported regions, see Use foundation models.

The Workiva connector is now available in Lakeflow Connect in Beta. Workspace admins can control access to this feature from the Previews page.

The connector ingests audit activity, users, and roles from your Workiva organization into Databricks. Authentication uses Workiva OAuth2 client credentials.

See Workiva connector.

Sharing managed Iceberg tables in Databricks-to-Databricks sharing and open sharing is now generally available. Providers can now also share managed Iceberg tables to external Iceberg clients. See Add managed Iceberg tables to a share and Read shared managed Iceberg tables.

You can now upload files to Genie Code to use as context for the current chat. See Attach files.

OpenSharing support for tables backed by default storage is generally available and on by default for most accounts. For most Enterprise or Premium tier accounts, Databricks will enable it automatically in mid-September 2026, and by early 2027 for the rest.

Until it is enabled for your account, an account admin can turn on the OpenSharing for Default Storage – Expanded Access feature from the Previews page in the account console. See Manage Databricks previews.

OpenSharing SecureConnect is generally available and available by default for accounts on the Premium plan. For accounts on the Enterprise plan, Databricks will enable it automatically in mid-September 2026, and by early 2027 for the rest.

Until it is available for your account, an account admin on the provider side can turn on the OpenSharing SecureConnect preview from the Previews page in the account console. See Share data behind a firewall with SecureConnect and Manage Databricks previews.

Google Gemini 3.7 Flash is now available on Unity Gateway for fast, cost-efficient everyday tasks. Access it through the same governed API as other models, with centralized permissions, guardrails, spend controls, and observability, and switch models without changing application code.

Customers are responsible for ensuring their compliance with applicable terms.

To query the model and see supported regions, see Use foundation models.

Smart Routing (Beta) automatically picks the right model and agent harness for each task, based on complexity, permissions, and budget. It shifts routine work to lower-cost models and reserves frontier models for hard problems, and every routing decision is visible and auditable. Smart Routing works with Claude Code and Codex when you run them through the Unity Gateway CLI or Omnigent, and routes across both proprietary and open models. Only Omnigent can route across coding harnesses, not just models. In internal benchmarks, it matched frontier-level quality while cutting overall task cost by more than 30%.

See Select models or use Smart Routing.

The SQL alert task in Lakeflow Jobs now supports all compliance security profile standards that Databricks supports and is available by default for workspaces with the compliance security profile enabled.

Use the task to evaluate a Databricks SQL alert as part of a Lakeflow Job. The task returns its evaluation state as a task output value, so downstream tasks can branch on the result.

See SQL alert task for jobs.