Borderless Lakehouse cross-cloud caching and connections
Today, we are excited to announce enhancements to the borderless Lakehouse, our answer to how data engineers, data scientists, and increasingly, AI agents, can query governed data directly where it lives.
To reason accurately and automate complex enterprise workflows, agents and data consumers of all types need fast, unified access to an organization's complete data estate, joining customer records, transaction logs, and operational telemetry across clouds. However, modern enterprise data is rarely confined to a single location; data estates often span Amazon S3, Azure Data Lake Storage (ADLS), Google Cloud Storage, operational databases, and SaaS platforms like Salesforce, SAP, and Workday. Historically, uniting these distributed datasets required brittle ETL pipelines, duplicated storage, and prohibitive cross-cloud data transfer costs.
We introduced the borderless Lakehouseearlier this year to let organizations query and activate data in place across clouds. By adopting the Apache Iceberg REST catalog specification, we federate directly to...
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