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How Unity Catalog Managed Tables Automate Performance at Scale

Sujitha
Databricks Employee
Databricks Employee

Unity Catalog (UC) managed tables combine strong governance with seamless interoperability across tools. Since the data sits in the customer-owned cloud storage, organizations retain full control over its physical location, while benefiting from Databricks’ built-in intelligence and automation.

Today, UC managed tables are the most commonly used table type in Databricks; two out of every three UC tables are managed. This adoption reflects its ability to simplify operations, reduce costs, and improve performance at scale.

With UC managed tables, organizations can be confident they are always using the latest table features. These tables are automatically upgraded, and unlike other table types, they understand usage patterns, allowing new capabilities to be enabled safely and incrementally, without manual intervention.


Image shows the AI-powered data optimization lifecycle. The model learns from table data and query patterns, predicts the best optimizations, runs them automatically, and observes changes to table data and query patterns in a feedback loop.

The structure of UC managed tables also enables advanced AI capabilities that weren’t possible before. Since all reads and writes route through Unity Catalog, Databricks can intelligently optimize data based on actual usage, improving query performance, reducing storage costs, and eliminating routine maintenance.

Key benefits include:

  • Automatic upgrades with the latest features
  • Self-maintenance with compaction, clustering, and vacuuming
  • Storage and compute cost savings through intelligent optimization
  • Secure access via Open APIs, even for non-Databricks clients
  • Faster queries across all clients, not just in Databricks

Continue to read more here.

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