Snowflake Unveils Cross-Layer Data Interoperability Framework to Tackle AI Data Silos

As companies adopt AI applications, their data is often scattered across data warehouses, data lakes and different compute engines, creating silos. Inconsistent field definitions and business semantics also complicate model training, governance and cross-platform analytics. Snowflake has therefore built an interoperability framework around open formats and common standards to reduce data movement and duplicate management costs.

Snowflake has unveiled an Apache Iceberg-based cross-layer data interoperability framework that supports Iceberg v3. Through the open-source pg_lake project and its work to advance Apache Polaris and Open Semantic Interchange (OSI) standards, the framework is designed to preserve consistent governance and semantics when data is shared across platforms and engines. Related reports did not disclose a release date, investment amount or timetable for formal deployment.