Google Cloud Lakehouse for Apache Iceberg review
A managed Iceberg lakehouse for Google Cloud teams using BigQuery and open engines.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Google Cloud Lakehouse for Apache Iceberg is a managed lakehouse platform for analytical, transactional, streaming, and AI workloads built on open table formats. It is aimed at organizations that want managed Apache Iceberg tables, a serverless runtime catalog, Cloud Storage-based data management, and BigQuery integration while retaining access to open processing engines. Its read/write interoperability with Apache Spark, Flink, Hive, and Trino makes it suitable for teams with mixed data-engineering environments.
Pricing is usage-based and divided across metadata storage, table management, metadata access, and catalog federation metadata refresh. The Metadata storage free tier includes 1 GiB of metadata storage per month; additional metadata storage is charged under the Metadata storage plan. Table management covers automatic table storage optimization, adaptive file sizing, automatic clustering, garbage collection, and BigQuery metadata generation. Separate Class A and Class B metadata access categories distinguish write-oriented operations from read, get, and delete operations. This structure gives buyers several cost dimensions to monitor rather than one simple subscription tier.
The platform’s strongest fit is a Google Cloud estate centered on BigQuery, Cloud Storage, and managed Spark, with governance needs handled through Knowledge Catalog, table ACLs, and IAM-based access control. Streaming CDC into Iceberg tables and integrations with AlloyDB and Spanner extend its role beyond batch analytics. Cross-cloud catalog federation connects with AWS Glue, Databricks Unity Catalog, and Snowflake Horizon Catalog, while the REST Catalog API supports Iceberg-compatible workflows. Teams seeking a narrow, single-engine warehouse experience may find this broader, multi-engine architecture more than they need.
Google Cloud Lakehouse for Apache Iceberg pros and cons
- Where it wins
- Managed Iceberg tables with REST Catalog and BigQuery SQL
- Interoperability with Spark, Flink, Hive, and Trino
- Governance, CDC, automated maintenance, and federation features
- Where it doesn't
- No standalone free plan
- Usage-based pricing spans several charge categories
- Cross-cloud federation supports selected external catalogs
Google Cloud Lakehouse for Apache Iceberg fact sheet, pricing and score →
Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.
Last updated · How we research and update