Google Cloud Lakehouse for Apache Iceberg

cloud.google.com

From $0.04/mo Free plan WebLinuxAPISelf-hosted

Spec score 9.1 #1 of 17 in Ai Data Platforms

What it is

Google Cloud Lakehouse for Apache Iceberg is a web service for working with Apache Iceberg tables. Its listed capabilities include SQL analytics, ACID transactions, streaming ingestion, and a governance catalog, with both listed storage models and table-format categories supported. Charges are organized by metadata storage, table management, metadata access, and catalog federation refresh rather than a single stated plan price. Metadata storage includes 1 GiB free each month; additional storage starts at $0.04 per GiB per month. Table management starts at $0.12 per DCU-hour and includes storage optimization, adaptive file sizing, automatic clustering, garbage collection, and BigQuery metadata generation. Class A metadata access includes 5,000 free operations monthly, and Class B includes 50,000. Catalog federation metadata refresh lists 0 to 5,001 free operations per account each month. The service is paid overall and has no free plan, despite those component-level free allowances. Listed billing thresholds are above 5,001 operations for Class A and catalog refresh, and above 50,001 for Class B. Google was founded in 1998 and is headquartered in Mountain View, California.

Spec sheet

What it does: Google Cloud Lakehouse is a managed storage and governance layer for Apache Iceberg data, separating storage from compute and allowing shared access by analytics engines.Read 15 Oct 2026 · docs.cloud.google.com
API: The Lakehouse API is a serverless, highly available metastore API exposing REST resources for catalogs and data-sharing objects.Read 15 Oct 2026 · docs.cloud.google.com
Compliance: Google Cloud lists ISO 27001, ISO 27017, ISO 27018, ISO 27701, SOC 1/2/3, PCI DSS, FedRAMP, GDPR and HIPAA offerings or alignments.Read 15 Oct 2026 · cloud.google.com
License: The Apache Iceberg project is distributed under the Apache License 2.0; Google Cloud Lakehouse itself is a proprietary managed service.Read 15 Oct 2026 · github.com
Headquarters: Mountain View, California, United StatesRead 23 Sep 2026 · cloud.google.com
Founded: 1998Read 23 Sep 2026 · cloud.google.com
AI features: BigQuery ObjectRefs combine structured Iceberg data with unstructured objects for multimodal, vector and graph analytics.Read 15 Oct 2026 · cloud.google.com
Automated maintenance: Lakehouse can automate file sizing, compaction, clustering, garbage collection, partitioning and history-based optimization.Read 15 Oct 2026 · cloud.google.com
BigQuery analytics: BigQuery supports vectorized execution, partition pruning, multi-statement transactions and SQL DDL/DML over Lakehouse Iceberg tables.Read 15 Oct 2026 · cloud.google.com
Company founding and headquarters: Google says it was officially born in 1998 and moved its headquarters to Mountain View, California; LinkedIn lists Mountain View as headquarters.Read 15 Oct 2026 · about.google
Company size: LinkedIn lists Google as a public software-development company with more than 10,001 employees.Read 15 Oct 2026 · linkedin.com
Cross-cloud federation: Preview federation can expose data cataloged in AWS Glue, Databricks Unity Catalog and Snowflake Horizon Catalog to BigQuery and Spark without moving the data.Read 15 Oct 2026 · cloud.google.com
Deployment model: Lakehouse runtime catalog is fully managed and removes the need to operate a self-hosted Hive Metastore.Read 15 Oct 2026 · docs.cloud.google.com
Developer documentation: Google provides introductory tutorials, quickstarts, reference material, code samples, engine-specific guides and troubleshooting documentation.Read 15 Oct 2026 · docs.cloud.google.com
Governance: Knowledge Catalog integration supports centralized governance policies, semantic search, lineage and quality checks across engines.Read 15 Oct 2026 · docs.cloud.google.com
Infrastructure as code: The Google Terraform provider provisions Lakehouse runtime catalog resources, including Iceberg REST catalog endpoints.Read 15 Oct 2026 · docs.cloud.google.com
Interoperability: The Iceberg REST catalog provides read and write interoperability among BigQuery, Managed Service for Apache Spark, Spark, Flink, Trino and other compatible engines.Read 15 Oct 2026 · cloud.google.com
Legal entity: Google Cloud's contracting-entity page identifies Google LLC for the United States and other uncovered locations.Read 15 Oct 2026 · cloud.google.com
Limit: API access: The BigQuery tabledata.list method cannot retrieve rows directly from runtime-catalog tables.Read 15 Oct 2026 · docs.cloud.google.com
Limit: cost visibility: BigQuery dry runs can report zero processed bytes for runtime-catalog queries even though the executed query incurs processing cost.Read 15 Oct 2026 · docs.cloud.google.com
Limit: orchestration and scheduling: TrustRadius reviewers report that orchestration and scheduled-query workflows can be awkward and require practice.Read 15 Oct 2026 · trustradius.com
Limit: query performance: Google warns that BigQuery queries over runtime-catalog tables may be slower than queries over standard BigQuery tables.Read 15 Oct 2026 · docs.cloud.google.com
Limit: support: Gartner's displayed dislikes include frustration when working with Google support.Read 15 Oct 2026 · gartner.com
Limit: table operations: The runtime catalog does not support table renaming, clustering, extract jobs, database views or Iceberg views.Read 15 Oct 2026 · docs.cloud.google.com
Open REST interface: The Iceberg endpoint implements the open-source Apache Iceberg REST Catalog API and supports credential vending for fine-grained access.Read 15 Oct 2026 · docs.cloud.google.com
Praise: scale and SQL: TrustRadius reviewers repeatedly praise fast complex SQL, large dataset handling, partitioning, scheduling, the SQL editor and BigQuery's suitability for ETL.Read 15 Oct 2026 · trustradius.com
Praise: speed and integration: Gartner reviewers describe BigQuery as fast, scalable and well integrated with Google Analytics for customer and marketing analysis.Read 15 Oct 2026 · gartner.com
Prerequisites: REST catalog setup requires an enabled Google Cloud project with billing, the BigLake API enabled and appropriate IAM roles.Read 15 Oct 2026 · docs.cloud.google.com
Rating on Gartner Peer Insights: 4.5 out of 5 from 448 ratingsRead 15 Oct 2026 · gartner.com
Rating on TrustRadius: 8.8 out of 10 from 319 reviewsRead 15 Oct 2026 · trustradius.com
Release: AWS Glue federation: On June 5, 2026 Google announced preview federation with AWS Glue catalogs.Read 15 Oct 2026 · docs.cloud.google.com
Release: BigQuery writes: On June 25, 2026 Google announced preview BigQuery DML, DDL and automatic table management for runtime-catalog Iceberg tables.Read 15 Oct 2026 · docs.cloud.google.com
Release: Snowflake federation: On July 13, 2026 Google added Snowflake Horizon Catalog as a preview remote catalog provider.Read 15 Oct 2026 · docs.cloud.google.com
Security controls: Google Cloud states that data is encrypted in transit and at rest and that access to encryption keys is audited.Read 15 Oct 2026 · cloud.google.com
Spark acceleration: Google advertises a vectorized Lightning Engine that accelerates Spark execution by up to 4.5 times without code changes.Read 15 Oct 2026 · cloud.google.com
Streaming and CDC: Google documents BigQuery streaming ingestion and change-data replication into Iceberg tables for real-time workloads.Read 15 Oct 2026 · cloud.google.com
Supported Iceberg versions: Iceberg V2 tables are generally available and V3 tables are previewed; V1 tables must be upgraded.Read 15 Oct 2026 · docs.cloud.google.com

Plans and prices

Metadata storage free tier Priced on request Free tier includes 1 GiB of metadata storage per month 1 GiB metadata storage Read 20 Sep 2026 · cloud.google.com

Metadata storage Priced on request Starting at $0.04 per GiB per month 1 GiB free metadata storage included Read 20 Sep 2026 · cloud.google.com

Table management Priced on request Starting at $0.12 per DCU-hour Automatic table storage optimization · Adaptive file sizing · Automatic clustering · Garbage collection · BigQuery metadata generation Read 20 Sep 2026 · cloud.google.com

Class A metadata access Priced on request Above 5,001 operations per month per account 5,000 operations free per month Read 20 Sep 2026 · cloud.google.com

Class B metadata access Priced on request Above 50,001 operations 50,000 operations free per month Read 20 Sep 2026 · cloud.google.com

Catalog federation metadata refresh Priced on request Above 5,001 operations per month per account 0 to 5,001 operations free per month per account Read 20 Sep 2026 · cloud.google.com

Metadata storage included tier Free 1 GiB per month Lakehouse runtime catalog metadata Read 15 Oct 2026 · cloud.google.com

Metadata storage overage $0.04 a month per GiB per month metadata beyond included 1 GiB Read 15 Oct 2026 · cloud.google.com

Lakehouse table management $0.12 a month per DCU-Hour automatic file sizing · clustering · garbage collection · BigQuery metadata generation Read 15 Oct 2026 · cloud.google.com

Class B metadata access $0.90 a month per million operations above 50,001 read · delete · getIamPolicy Read 15 Oct 2026 · cloud.google.com

Class A metadata access $6 a month per million operations above 5,001 per month/account create · register · list · update · setIamPolicy Read 15 Oct 2026 · cloud.google.com

Every Google Cloud Lakehouse for Apache Iceberg plan and price →

Strong points and limits

Strong points

Supports SQL analytics and ACID transactions.
Includes streaming ingestion and a governance catalog.
Metadata storage includes 1 GiB free each month.
Table management includes optimization and clustering capabilities.

Limits

No free plan, despite component-level free allowances.
Metadata storage beyond 1 GiB starts at $0.04 per GiB monthly.
Table management starts at $0.12 per DCU-hour.

Who it suits

It suits teams working with Apache Iceberg tables that need SQL analytics, streaming ingestion, transactions, and catalog governance. Its component-based billing details may matter to organizations estimating metadata and table-management usage.

Verdict

The service combines Iceberg table work with analytics, ingestion, and governance capabilities. Its listed charges vary by storage, management, and metadata operations, and no overall plan price is stated.