Restore a deleted Unity Catalog metastore with the REST API (Public Preview)
Databricks account admins can now restore a deleted Unity Catalog metastore by ID using the REST API for up to 5 days after deletion in public preview.
86 releases · 5 this month
Databricks account admins can now restore a deleted Unity Catalog metastore by ID using the REST API for up to 5 days after deletion in public preview.
You can now run read queries on tables protected by row filters, column masks, and attribute-based access control (ABAC) policies with Lakehouse//RT. See Fine-grained access control .
A schema can now hold up to 1,000 Unity Catalog secrets, and a metastore up to 10,000, up from 100 and 1,000. The limits apply to Databricks-managed secrets and secrets backed by AWS Secrets Manager.
Request for access is now generally available. Users can request privileges on Unity Catalog objects from anywhere in Databricks and track request status in Catalog Explorer. See Access requests .
Users can now edit files stored in Unity Catalog volumes directly within the Databricks workspace file editor, eliminating the need for manual downloads and uploads.
Unity Catalog Files API 3.0 is in beta, adding support for multipart uploads for files larger than 5 GB and conditional operations to prevent unintended changes.
The READ METADATA privilege now supports all compliance security profile standards supported by Databricks and is available by default for workspaces with the compliance security profile enabled. For a full list of supported compliance standards, see Compliance security profile .
Data Classification now detects 50 new classes of sensitive data, along with new regional support for 16 countries and regions: Payment card and financial data : Card security codes, card expiration dates, card track data, card PINs, SWIFT codes, and credit scores.
The Data Classification API and its Terraform resource are now generally available. Auto-tagging configuration ( auto_tag_configs ) remains in Public Preview . See the API reference .
You can now create a ready-to-use packaged clean room with an approved identity resolution provider, such as Acxiom, Adstra, LiveRamp, or The Trade Desk, in one step from the Clean Rooms page. The provider is preconfigured as the package provider, so you can add your data and run the provider's analysis right away.
Tag propagation in Unity Catalog is in Beta . When you enable tag propagation for a governed tag, Unity Catalog uses lineage to automatically apply that tag to derived tables and views whenever a supported operation runs, such as CREATE TABLE AS SELECT , CREATE VIEW , INSERT INTO ... SELECT , or MERGE .
In mid-November 2026, JDBC Unity Catalog connections, including support for SSL certificates, will be available by default for workspaces with the compliance security profile enabled. Use JDBC Unity Catalog connections to connect to external databases with a custom JDBC driver, with access governed by Unity Catalog. See JDBC connection .
The Discover page and domains are now generally available. Discover is a curated browsing experience that helps users find assets across Databricks without requiring deep knowledge of catalog hierarchies.
In November 2026, the remote_query table-valued function will be available by default for workspaces with the compliance security profile enabled. Use remote_query to run queries on external databases in their native SQL syntax, with credentials from a Unity Catalog connection. See Query external databases using the remote_query function .
JDBC Unity Catalog connections are now generally available on serverless compute, Databricks Runtime 19 and above, and SQL warehouses 2025.40 and above, including support for SSL certificates. OAuth M2M authentication remains in Beta. See JDBC connection .
Cross-engine attribute-based access controls (ABAC) is now generally available. Supported external engines can read Unity Catalog managed tables with ABAC policies, row filters, and column masks enforced by Databricks serverless compute. See Cross-engine attribute-based access controls (ABAC) for requirements, supported clients, and serverless compute costs.
Attribute-based access control (ABAC) row filters and column masks now extend to views, in addition to tables. This lets you use ABAC policies to control access to sensitive data exposed through views. Account admins can enable the ABAC on Views preview from the account console's Previews page. This feature requires Databricks Runtime 19 or above.
This feature is in Beta . Starting in Databricks Runtime 19, you can use time travel on qualifying Unity Catalog managed tables while enforcing ABAC row filter and column mask policies. See Time travel with ABAC policies .
You can now invite OpenSharing recipients by email instead of exchanging a sharing identifier or credential file. OpenSharing emails the recipient a secure activation link to connect and read the shared data. Email sharing is in Beta . See OpenSharing by email .
Metastore-level ABAC policies are in Beta in Unity Catalog. You can now attach an ABAC policy (row filter, column mask, GRANT, or DENY) at the metastore level, so a single policy applies across every catalog in the metastore, including catalogs created later.
You can now use a single VARIANT function to mask columns of type ARRAY and MAP , in addition to STRUCT and other types. This requires Databricks Runtime 19 or above. See Masking multiple column types with a single function .
Data Classification can now scan Unity Catalog views in addition to tables, classifying columns for sensitive data using the same detection engine. This is a Beta feature. See Classify views .
Sharing and reading foreign Iceberg tables with OpenSharing is now generally available. Providers can share Iceberg tables federated from foreign Iceberg catalogs using Lakehouse Federation, including to recipients using external Iceberg clients.
External secrets connect a Unity Catalog schema to AWS Secrets Manager. The secrets appear in Unity Catalog as read-only securable objects that you govern with Unity Catalog privileges. Databricks reads their values from AWS Secrets Manager on demand. See External secrets in Unity Catalog .
ABAC DENY policies are in Beta in Unity Catalog. DENY policies can be used to explicitly deny the MANAGE ACCESS CONTROL privilege to prevent specified principals, including object owners, from performing access-management operations. They always take precedence over any grant. For details, see ABAC DENY policies (Beta) .
ABAC GRANT policies for models, model services, model provider services, Model Context Protocol (MCP) services, and agent services are now generally available. These policies dynamically grant Unity Catalog privileges to securable objects whose governed tags match a condition, instead of granting privileges on each object individually.
You can now publish, govern, and share agent skills with Unity Catalog. A skill is a first-class Unity Catalog securable ( catalog.schema.skill ) that follows the SKILL.md specification , so you register it once and control who can discover, use, and update it with the same permissions, tags, and audit that protect your tables.
You can now use OpenSharing to share foreign Delta tables, which are Delta-format tables registered in a foreign catalog such as OneLake, a Hive metastore, or AWS Glue. Providers add foreign Delta tables to a share, and recipients access the shared data in read-only format.
The INSERT , UPDATE , and DELETE privileges are in Beta in Unity Catalog. These privileges are least-privilege alternatives to MODIFY that let you grant write access to a table's data without also granting the ability to change its schema or other metadata. The privileges require Databricks Runtime 18.1 or above.
Context attributes for attribute-based access control (ABAC) policies are in Beta. You can now write Unity Catalog ABAC policy conditions that target the context of a request, such as which OAuth application is calling ( request.client_id ) and whether the request runs on behalf of a user ( request.is_on_behalf_of ).
We are thrilled to announce Unity Catalog 0.6.0 release, which includes exciting new features, many bug fixes, and improvements. A huge thank you to the awesome community who made this release possible!
Role-based access control (RBAC) is now generally available. RBAC lets users assume a role in Databricks. When a user assumes a role, only that role's permissions apply, rather than the user's accumulated permissions. This enables exclusive access.
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.
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 .
OpenSharing support for tables backed by default storage is now generally available and is being enabled by default for accounts on a rolling basis. Providers can share these tables with any recipient, whether open or Databricks, including recipients that use classic compute.
You can now use Pages to give business terms, acronyms, and KPIs a single governed definition. Part of Unity Catalog semantics , Pages form the human-modeled layer of the Genie Ontology that Genie One draws on to ground its answers. See Pages .
ABAC GRANT policies dynamically grant Unity Catalog privileges to securables whose governed tags match a condition. These policies were previously only available for models, but now also support model services, model provider services, Model Context Protocol (MCP) services, and agent services. All supported types are in Beta.
The READ METADATA privilege is now generally available in Unity Catalog. READ METADATA provides read-only visibility into the same metadata available to the object's owner or a user with MANAGE , including security-sensitive information that BROWSE doesn't expose, such as privilege grants, row filters and column masks, and ABAC policies.
Tag automations are now in Beta . A tag automation assigns or removes governed tags on the Unity Catalog tables or volumes that match conditions you define, so tags stay accurate as your data and metadata change.
HTTP connections in Unity Catalog are now generally available at the schema level. You can create an HTTP connection inside a schema instead of only at the metastore level.
Secrets in Unity Catalog is now generally available. You can store, govern, and access secrets as securable objects in Unity Catalog. A Unity Catalog secret uses the three-level namespace ( catalog.schema.secret ) and is governed by Unity Catalog privileges, so you can apply the same access controls and auditing that you use for other data assets.
Packaged clean rooms are now generally available. In a packaged clean room, a provider supplies notebooks, JARs, and data that a consumer runs against their own data without seeing the provider's code or data assets. See Packaged clean rooms .
Registering Python user-defined table functions (UDTFs) in Unity Catalog is now generally available in Databricks Runtime 18. A Unity Catalog Python UDTF is a governed function that returns a table, invoked in the FROM clause of a SQL statement to return multiple rows and columns.
The system.tags.governed_tags system table is in Beta . This table contains a record for each governed tag key in your account, including customer-created and system-generated tags. Use it to programmatically determine which tags in your account are governed. See Governed tags system table reference .
Governance Hub is in Beta . Governance Hub is a centralized, account-level UI in the account console for monitoring governance across your Databricks account. It provides a unified view of data health and coverage, AI usage and spend, and cost drivers, with prioritized insights and recommendations. All views respect existing permissions.
Register Scala and Java user-defined functions (UDFs) in Unity Catalog and reuse them across notebooks, jobs, and SQL warehouses with Unity Catalog governance. Reuse existing JVM logic and get better performance than Python UDFs on all compute, including serverless. See Scala and Java user-defined functions (UDFs) in Unity Catalog .
Data Classification is now available by default for workspaces with the compliance security profile enabled and either C5, TISAX, or IRAP controls selected.
Streaming reads from OpenSharing tables now support the Trigger.AvailableNow trigger. This trigger captures the shared table's current version when it starts, processes all available data across one or more micro-batches (honoring maxFilesPerTrigger and maxVersionsPerRpc ), and then stops, which is well suited to scheduled, batch-like incremental...
You can now store, govern, and access secrets as securable objects in Unity Catalog. A Unity Catalog secret uses the three-level namespace ( catalog.schema.secret ) and is governed by Unity Catalog privileges, so you can apply the same access controls and auditing that you use for other data assets. See Secrets in Unity Catalog .
You can now govern Databricks-hosted LLMs in Unity Catalog using model services , currently in Beta. A model service is a Unity Catalog securable that represents a governed LLM endpoint, so you can define an endpoint once and share it across workspaces using Unity Catalog privileges, instead of duplicating endpoints per workspace.
The 0.4.0 release of Unity Catalog AI includes several improvements, including expanded Databricks client options and dependency/security improvements. Artifacts in this release unitycatalog-ai unitycatalog-langchain unitycatalog-openai Major Changes Warehouse ID Support in DatabricksFunctionClient : For workspaces where serverless compute is unavailable or...
We are excited to announce Unity Catalog 0.4.0 release which includes exciting new features and many bug-fixes and improvements. A huge thank you to the awesome community who made this release possible!
Unified governance for data and AI assets.
Other Databricks products: Agent Bricks and Mosaic AI, AI/BI and Genie, Databricks Apps, Databricks Data Intelligence Platform, Databricks SQL, Delta Lake, Lakebase, Lakeflow, MLflow
| Release-notes page | Site | Feed |
|---|---|---|
| Unity Catalog OSS releases github.com | github.com | RSS |
| 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 |