Iceberg vs Closed Formats in Snowflake, BigQuery and Redshift

Onehouse CEO Vinoth Chandar argues that although Snowflake, BigQuery, Redshift, Databricks, AWS, and Google have substantially expanded Apache Iceberg support since 2024, the major cloud warehouses still default many workloads to proprietary native table formats and continue introducing important capabilities there first. He highlights gaps such as Snowflake’s unsupported vector and file types on Iceberg tables, BigQuery’s AI indexing and governance limitations for Iceberg, and Redshift’s continuing investment in native storage optimizations despite growing Iceberg interoperability. Chandar calls for vendors to publish retirement or transition plans for closed formats, make open tables the standard choice for appropriate new workloads, provide clear migration support for existing data, and disclose feature trade-offs. At the same time, he acknowledges that Iceberg cannot immediately standardize every storage innovation and describes it as a practical cross-engine baseline rather than the sole format for all new features. He distinguishes between proprietary, rebuildable engine optimizations over open data and systems in which the only usable copy remains locked in a closed format, concluding that lasting openness depends on interoperability, transparent vendor commitments, and customers scrutinizing the portability of their data.

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