Iceberg V3 Geometry, One Year Later: From Standards to Implementations

The efforts to integrate geospatial data as a first-class citizen within the open data ecosystem have seen significant progress, particularly through the implementation of GeoParquet and Apache Iceberg V3. These standards aim to make geospatial data open, governed, and queryable across various engines, optimizing metadata rather than relying on specialized spatial infrastructure. A public testbed was created to evaluate the extent to which this promise has been realized across different data engines. Snowflake emerged as a leader, successfully implementing Iceberg V3's native geometry and spatial predicates, while DuckDB is nearing full support. Other engines, such as BigQuery and Databricks, face challenges mainly related to supporting the new geometry types rather than the Iceberg V3 format itself. The ongoing advancements signify a shift towards native geometry support, with Snowflake showcasing a complete implementation and other platforms expected to follow suit. This development is crucial for removing barriers between GIS and modern cloud analytics, ensuring geospatial data can be seamlessly integrated into existing analytical workflows.