Google BigQuery Previews Native Cross-Region SQL Queries
Google BigQuery is now previewing native cross-region SQL queries, allowing users to run federated analytics across globally distributed datasets. The feature eliminates the need for manual ETL or data duplication between regions. This significantly simplifies building multi-region applications that need to balance performance, compliance, and operational overhead.
Previously, analyzing datasets spread across different geographic regions in BigQuery required creating complex and costly ETL pipelines to centralize the data first. This introduced delays and complexity, hindering timely ad-hoc analysis for multinational corporations needing a unified view of their business. The new "global queries" feature, currently in preview, allows a single standard SQL query to join tables across different regions, like `us-central1` and `europe-west1`, without any data movement preparation. This functionality is designed for use cases such as consolidated reporting and cross-regional analysis, simplifying the architecture for multi-region BigQuery setups. Behind the scenes, BigQuery orchestrates the cross-region execution by running sub-queries in each remote region and transferring only the necessary filtered results to a primary execution location for the final join. This zero-ETL approach helps maintain data residency for compliance with regulations like GDPR, as the raw data remains in its original location. The feature is disabled by default to prevent accidental data transfers and costs. Administrators must explicitly opt-in by enabling it for a project, and users need special permissions to run a global query. Developers also specify the execution location, giving them control over where the data is ultimately processed. Costs for a global query include the compute cost for subqueries in remote regions, the final query's compute cost in the primary region, and data replication charges for the temporary data movement between regions. This is a distinct feature from BigQuery's existing federated queries, which connect to external databases like Cloud SQL.
