Row Filters
Recent items mentioning Row Filters across the Databricks ecosystem — releases, news, videos, and community Q&A. Updated hourly.
Unity Catalog's row-level security (RLS) is being leveraged for multi-tenant data isolation, as seen with Barracuda's Genie integration for security log analysis 1. Databricks recently published a blog post detailing what RLS is, emphasizing its role in filtering table data by user identity, role, or session context to ensure authorized access across various tools 3. Furthermore, Unity Catalog's fine-grained access controls, including RLS, are now consistently enforced across Databricks and external engines like Apache Spark 2.
Generated daily from the 4 most recent items mentioning Row Filters. Click any [N] to jump to the source.
How to ground Genie Agents in both structured data and documents without losing governance
Genie Agents can be grounded across both structured data and unstructured Unity Catalog Volumes, allowing a single agent to answer questions across all your enterprise data. By anchoring governance at the catalog layer with features like Automatic Identity Management, Row Filters, and Column Masks, the agent runs as the user's identity so every answer
Introduces catalogs.yml v2 support, a `skip_optimize` config for opting out of post-materialization OPTIMIZE, and Rust kernel backend for SQL warehouses. Fixes numerous incremental model bugs around constraints and tags, but now requires `--full-refresh` to apply changes to primary/foreign key expressions.
Barracuda makes security logs conversational with Genie
Barracuda Managed XDR now uses Genie to enable natural language search of security logs, letting analysts investigate threats across thousands of customers without SQL or schema expertise. Unity Catalog's row-level security enforces tenant isolation at the data layer, ensuring safe multi-tenant threat detection.
NewsUnity Catalog Fine-Grained Access Controls on External Engines
Unity Catalog enables fine-grained access controls (FGAC) defined once to be enforced consistently across Databricks and external engines like Apache Spark. External engines can also create and write to UC-managed tables, benefiting from centralized governance, automatic optimization, and transactional safety.
What is row-level security?
Row-level security filters table data by user identity, role, or session context, ensuring each person sees only the rows they are authorized to access across dashboards, notebooks, APIs, and other tools. Effective RLS depends on clear access logic, reliable keying columns, separate read/write controls, and testing across multiple user roles, and is most effective as part of layered governance.
Transforming solar and wind maintenance reports with Genie and AI agents
Plenitude now converts unstructured solar and wind maintenance PDFs into a unified, queryable data model using Databricks Genie and AI agents. This enables natural-language querying and visualizations across plants, accelerating multi-plant analysis and laying the groundwork for predictive maintenance.
Introducing Cross-Engine ABAC
Unity Catalog now enforces attribute-based access controls (ABAC) on external engines, allowing you to define tag-based row filters and column masks once for enforcement from any engine. This centralized governance at the catalog layer, built on Iceberg REST Catalog scan APIs, ensures policies are enforced before data reaches the engine.
v1.12.0 adds metric views, row filters, and Python UDFs as new materializations, along with SCHEDULE EVERY and TRIGGER ON UPDATE refresh modes for materialized views and streaming tables. databricks_tags now merge additively across hierarchy levels instead of child replacing parent (breaking change), and the release includes fixes for metric view validation, pydantic v1 compatibility, and streaming table refresh scheduling.
Backstage with Lakebase, part 2
Lakebase enables running production OLTP applications like Backstage on a serverless Postgres surface within Databricks, offering 1-second database branching and sub-4-second point-in-time recovery for schema migrations. Unity Catalog unifies governance for operational databases, providing single SQL query auditing, automatic row-level security propagation to branches, and zero-ETL cost attribution for FinOps.
TutorialsGoverned Tags & Data Classification in Databricks | ABAC Foundations
Databricks now offers governed tags and automated data classification to identify sensitive information like PII. This enables Attribute-Based Access Control (ABAC) policies for masking or hiding data based on user roles, without altering query patterns.