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cloud.google.com·4d ago
Cloud & Infrastructure
Google Cloud Blog·16h ago·5 min read
Accelerating the borderless Lakehouse: Announcing preview of cross-cloud caching
TL;DR
Google Cloud has introduced cross-cloud caching for its borderless Lakehouse, enabling faster access to governed data across multiple cloud environments. This enhancement allows data engineers and AI agents to efficiently query and utilize diverse datasets in real-time.
✦ Why It Matters
Evaluate your data architecture today to incorporate cross-cloud caching for improved data access speed.
Key Takeaways
- Implement cross-cloud caching to enhance query performance.
- Utilize BigQuery's sub-file block granularity for efficient data transfer.
- Ensure data security with default encryption for cached data.
- Leverage caching to minimize costs in cross-cloud analytics.
How It Works
Cross-cloud caching operates at the sub-file block level, allowing BigQuery to transfer only the necessary data chunks instead of entire files. This method significantly reduces network transfer and latency, especially for repeated queries.
Cached data is encrypted at rest, ensuring security, while freshness checks prevent stale reads by verifying data updates before use.