Announcing MCP Toolbox Java SDK v1.0: Agentic data access for the enterprise
cloud.google.com·6d ago
Cloud & Infrastructure
Google Cloud Blog·Jul 29·5 min read
The borderless Lakehouse: Bring AWS, Databricks and Snowflake data to your AI agents
TL;DR
Google Cloud has launched the borderless Lakehouse, enabling AI agents to access and analyze data across AWS, Databricks, and Snowflake without moving it. This innovation enhances real-time decision-making and reduces costs associated with data transfer and management.
✦ Why It Matters
Start integrating your data across clouds today to enhance AI-driven decision-making and reduce costs.
Key Takeaways
- Utilize the borderless Lakehouse for real-time data access across clouds.
- Implement zero-copy analytics to avoid data duplication costs.
- Leverage Cross-Cloud Interconnects for predictable data transfer pricing.
- Integrate Knowledge Catalog for enhanced AI decision-making context.
How It Works
The borderless Lakehouse uses Apache Iceberg to federate data catalogs across platforms like AWS Glue and Snowflake, allowing seamless querying of remote data. This eliminates the need for data movement and complex ETL processes, enabling real-time analytics.
Cross-Cloud Interconnects provide dedicated, low-latency connections, while intelligent caching reduces repeated data transfers, optimizing performance.