Expanded interoperability with Unity Catalog Open APIs

· Source: Databricks · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics, Cloud Computing & IT Infrastructure · Depth: Intermediate, short

Summary

Unity Catalog (UC) has expanded its open lakehouse capabilities with new features for external access to managed tables and credential vending, now in Beta and Generally Available (GA) respectively. UC managed tables, which utilize Predictive Optimization and Liquid Clustering for up to 20x faster queries and 50% lower storage costs, can now be created, read, and written to by external engines like Apache Spark, Flink, and DuckDB with full transactional safety and streaming support. This is enabled by credential vending, a GA feature that issues short-lived, scoped credentials to external engines on demand, supporting machine-to-machine (M2M) OAuth and automatic token refresh. Volume credential vending is also in Public Preview, extending this secure access to unstructured data. Delta Kernel, an open-source library, simplifies integration for connector developers, fostering a growing ecosystem.

Key takeaway

For data platform teams seeking to unify data governance across diverse compute engines, Unity Catalog's new external access to managed tables and credential vending capabilities are critical. You can now enable external engines to securely create, read, and write to optimized Delta tables and volumes, ensuring centralized control and auditability without data duplication. Consider enrolling in the Beta and implementing credential vending to enhance security and interoperability across your data and AI platforms.

Key insights

Unity Catalog now offers secure, optimized external access to managed tables and unstructured data via credential vending.

Principles

Method

Unity Catalog issues short-lived, scoped credentials via credential vending, allowing external engines to authenticate and access managed tables and volumes, with policies enforced centrally and M2M OAuth support.

In practice

Topics

Code references

Best for: CTO, VP of Engineering/Data, Director of AI/ML, Data Engineer, MLOps Engineer, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by Databricks.