Here is what moved on Databricks in the last 7 days.

New features

• Genie One skills now support multiple files and folders Genie One skills can now include multiple files and sub-folders. Each skill can use folders up to three levels deep and up to 50 files or folders, and skills can load text files only. read it

• SQL adds MATCH_RECOGNIZE for row-pattern matching The blog introduces MATCH_RECOGNIZE as a SQL feature for detecting patterns across rows, described as similar to regex for rows. Learners working with event-style data, such as login attempts, should know the syntax exists before building pattern detection logic another way. read it

• Unity Gateway API and developer tools are generally available The Unity Gateway API is generally available for managing model services, model provider services, and MCP services. Create, read, update, list, and delete operations are supported across Terraform, the Databricks CLI, and the listed Databricks SDKs; Declarative Automation Bundles support through the CLI is in Beta. read it

• Unused OAuth client secrets are deleted after 90 days Databricks now deletes a service principal's OAuth client secret after 90 days without use. If that deleted secret is still needed, create a new OAuth secret. read it

• READ METADATA will be default for compliance profile workspaces READ METADATA will be available by default for workspaces with the compliance security profile enabled in mid-October 2026. The privilege gives read-only access to object metadata that BROWSE does not show, including privilege grants, row filters and column masks, and ABAC policies, so users who inspect or debug access controls should understand the difference. read it

• On-demand state repartitioning added for Structured Streaming Databricks announced on-demand state repartitioning for Apache Spark Structured Streaming on Databricks. The entry is aimed at people running stateful Structured Streaming queries in production. read it

• counter_diff is now available for SQL window calculations Databricks added the counter_diff window function for time-series counter data. It calculates differences between consecutive cumulative counter values and handles counter resets, and is available in Databricks SQL and Databricks Runtime 19 and above. read it

• Metric view window measures can use a numeric index column Window measures in metric views now support unitless offsets and trailing or leading ranges on a consecutive integer order column. Authors can use a numeric index for non-calendar periods such as fiscal weeks or 4-4-5 periods. read it

• Open sharing reaches foreign catalogs, Iceberg included A provider can share Iceberg tables, schemas and tables that live in a federated catalog without copying anything into Databricks. The compute and storage cost of materialising them stays with the provider. Generally available. read it

• Standard performance mode is available for one-time Jobs API runs The Jobs API can now set performance_target to STANDARD for one-time runs. Apache Airflow's DatabricksSubmitRunOperator also supports this setting, so users who trigger one-time runs from Airflow can use it there too. read it

• OpenSharing sharing for foreign Iceberg tables is generally available Sharing and reading foreign Iceberg tables with OpenSharing is now generally available. Providers can add Iceberg tables federated from foreign Iceberg catalogs through Lakehouse Federation to a share, including for recipients that use external Iceberg clients. read it

• DeepSeek V4.1 Flash is available on Unity Gateway DeepSeek V4.1 Flash is available on Unity Gateway with text and image inputs. Users can access it through Foundation Model APIs and should check supported regions and applicable terms before using it. read it

Previews and beta

• ABAC policies can now apply at the metastore level in Beta Unity Catalog now has Beta support for attaching an ABAC policy at the metastore level. A row filter, column mask, GRANT, or DENY policy attached there applies across every catalog in the metastore, including catalogs created later, instead of being replicated per catalog. read it

• ABAC row filters and column masks can apply to views in beta ABAC row filters and column masks now extend to views, in addition to tables. Account admins can enable the ABAC on Views preview from the account console, and the feature requires Databricks Runtime 19 or above. read it

• Genie Slack replies can include chart images in preview When a Genie response includes a chart, Slack replies now show the visualization as an image. This is Public Preview; users who installed the Databricks Genie app for Slack before must reinstall it to enable the feature. read it

• Serverless jobs can restore run state into notebooks in preview Databricks can automatically capture a snapshot for eligible serverless compute job runs. In Public Preview, you can restore the Python variables and Spark session from that run into a new interactive notebook to debug a failure or explore results without rerunning the whole job. read it

New and rewritten concepts

• Lakebase behind an app, an agent or a feature store Attaching a Lakebase database to a Databricks App as a resource, what the platform creates for the app's service principal, why the schema has to be the app's own, and the other platform features backed by Lakebase.

• Lakebase change data feed, from Postgres into Delta Every insert, update and delete in a Lakebase schema recorded as rows of a Unity Catalog Delta table, read from the Postgres write-ahead log.

• Computes, autoscaling, scale-to-zero and high availability The Postgres computes behind a Lakebase branch, how they autoscale in capacity units, when they suspend to zero and what that costs a session, and how secondaries and read replicas differ.

• Connecting to Lakebase, roles and permissions How clients reach a Lakebase compute over TLS, the choice between one-hour OAuth tokens and Postgres passwords, and how Databricks identities become roles.

• The Data API and Postgres extensions A PostgREST-compatible HTTP interface generated from the schema, and the Postgres extensions Lakebase ships — pgvector, PostGIS, pg_stat_statements and the rest — including the beta search indexes.

• Lakebase, the Postgres inside Databricks A fully managed Postgres database in the Databricks platform, for the transactional workloads a lakehouse is the wrong shape for, sharing storage and governance with the lakehouse beside it.