Unity Catalog Fine-Grained Access Controls on External Engines
Key Takeaways
Demonstrates Unity Catalog fine-grained access controls on external engines using Databricks and Apache Spark
Original Description
See how Unity Catalog enforces row filters and column masks identically, whether you're querying from Databricks or from open-source Apache Spark running on a VM outside your workspace. This demo walks through defining ABAC policies once in UC, verifying enforcement on Databricks serverless SQL, then running the same query from OSS Delta-Spark on EC2 to show identical results. Finally, we demonstrate external engines creating and writing to managed tables with catalog-managed commits, fully governed and automatically optimized.
Learn more about Catalog Commits: https://www.databricks.com/blog/convergence-open-table-formats-and-open-catalogs-catalog-commits-generally-available
Watch on YouTube ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: ML Pipelines
View skill →Related Reads
📰
📰
📰
📰
I Built My Second ETL Pipeline. This Time, I Started Thinking Like a Data Engineer
Towards Data Science
JuiceFS Sync for PB-Scale Data Transfers: Resumable Sync, Encryption, and Bandwidth Control
Dev.to AI
How Airflow is using AI to make data engineering more resilient, not more complex
Medium · AI
What Can We Do When Memory Becomes the New Bottleneck in Data Engineering?
Towards Data Science
🎓
Tutor Explanation
DeepCamp AI