Google Cloud Introduces Cross-Engine Iceberg Support in BigQuery
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New BigQuery Iceberg support, highly actionable for GCP data engineers.
Google Cloud's preview of a serverless Iceberg REST catalog in BigQuery lets engines like Spark, Flink, and Trino share tables without duplication, while managed metadata and table maintenance reduce operational overhead. At Next '26, Google extended this to a cross-cloud lakehouse querying Iceberg across AWS, Azure, Databricks, and Snowflake, and introduced BigQuery ObjectRefs (GA) for combining structured Iceberg data with unstructured files for AI workflows. The Knowledge Catalog governance layer (preview) manages metadata and lineage, addressing the 'hidden tax' of Iceberg adoption.
Evaluate the serverless Iceberg REST catalog and ObjectRefs to unify data access and AI workflows across your multi-cloud lakehouse.
For a Solutions Architect focused on cloud infrastructure and data engineering, this reduces the friction of multi-engine lakehouse architectures and simplifies governance across clouds, directly impacting platform design and cost.
InfoQ Homepage News Google Cloud Introduces Cross-Engine Iceberg Support in BigQuery Cloud Google Cloud Introduces Cross-Engine Iceberg Support in BigQuery May 23, 2026 3 min read by Renato Losio Write for InfoQ Feed your curiosity. Help 550k+ global senior developers each month stay ahead. Get in touch Listen to this article - 0:00 Audio ready to play Your browser does not support the audio element. 0:00 0:00 Normal 1.25x 1.5x Like Reading list At the Apache Iceberg Summit last month, Google announced new interoperability features for Apache Iceberg in BigQuery