Cloud BigQuery

Serverless data warehouse that decouples storage and compute to run analytics at petabyte scale. Queries scale automatically with no infrastructure to manage, and SQL-based analytics works alongside built-in ML for forecasting, clustering, and generative AI tasks.

Trusted by enterprises such as Mattel and Shopify for unified data-to-AI workflows. BigQuery runs across multiple clouds and supports open formats like Apache Iceberg, differentiating it from single-cloud alternatives such as Redshift or Snowflake. Built on Google infrastructure including Colossus and Dremel, with 99.99% uptime SLA and built-in governance through Dataplex.

Key capabilities:

• Serverless SQL analytics with automatic scaling, on-demand or reserved capacity
• In-database ML: train and run models with SQL, integrate with Vertex AI for MLOps
• Streaming ingestion, continuous queries, and federation to external data sources without moving data
• Apache Iceberg and BigLake for open-format lakehouse use cases
• Cross-region replication and managed disaster recovery

Data teams consolidate siloed data for BI reporting, real-time dashboards, and predictive analytics. Data scientists run end-to-end workflows in Colab notebooks with BigQuery DataFrames or Spark. Engineers build event-driven pipelines with streaming inserts and Pub/Sub subscriptions. Migration from legacy warehouses like Teradata, Netezza, or Redshift is supported via BigQuery Migration Service.