Google Cloud serverless warehouse for petabyte-scale SQL analytics
BigQuery is Google Cloud's serverless, column-oriented data warehouse. Analysts query with standard SQL and pay for the storage and compute they use, so there are no clusters to size. Storage and compute are decoupled, streaming inserts arrive within seconds, and external tables can read data that was never loaded into the warehouse. Its machine-learning angle is BigQuery ML, which lets an analyst train and run models such as forecasting or classification with SQL, without moving data into another platform. The differentiator is scale without operations work, at the cost of per-query spending that rewards careful tuning.
Last updated: 2026-09-20. This site only provides an index; for exact features, pricing, and licensing, see the official website.
warehouse analytics, large-scale sql, event and log analysis, sql forecasting
If you're comparing similar products, check the alternatives below, or browse all tools in the AI Data Analysis category.
No. It is a serverless data warehouse first. Its machine-learning angle is BigQuery ML, which lets analysts train and run models such as forecasting or classification with SQL, but the platform itself is conventional analytics infrastructure.
Two main models exist: on-demand, where you pay for data scanned per query, and capacity, where you reserve slots. Flat-rate commitments and a free monthly allowance also exist. The bill depends heavily on how well tables are partitioned and clustered.
Yes. External and federated tables let BigQuery read from Cloud Storage, Bigtable and Spanner, and BigQuery Omni extends queries to data held in other clouds instead of copying it into the warehouse first.
Unified lakehouse platform for data engineering, analytics and AI
Microsoft business intelligence service with Copilot-assisted reporting
Visual analytics platform known for exploratory drag-and-drop charting
Open-source BI platform you can self-host with SQL-first dashboards