Row Filters
Recent items mentioning Row Filters across the Databricks ecosystem — releases, news, videos, and community Q&A. Updated hourly.
Unity Catalog now enforces attribute-based access controls (ABAC) on external engines, allowing for tag-based row filters and column masks defined once and enforced before data reaches the engine via Iceberg REST Catalog scan APIs 4. This extends to fine-grained access controls (FGAC) consistently across Databricks and external engines like Apache Spark, even when external engines create and write to UC-managed tables 1. Row-level security, which filters data by user identity or role, is highlighted as a key component of layered governance, requiring clear access logic and thorough testing 2.
Generated daily from the 4 most recent items mentioning Row Filters. Click any [N] to jump to the source.
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.
This release adds support for metric views, row filters, Python UDFs, and key-only Databricks tags. It also includes a breaking change where Databricks tags now merge additively across hierarchy levels.
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.