BigQuery reliability guide

Last reviewed 2023-08-05 UTC

BigQuery is Google Cloud's data warehouse platform for storing and analyzing data at scale.

Best practices

  • Introduction to reliability - reliability best practices and introduction to concepts such as availability, durability, and data consistency.
  • Availability and durability - the types of failure domains that can occur in Google Cloud data centers, how BigQuery provides storage redundancy based on data storage location, and why cross-region datasets enhance disaster recovery.
  • Best practices for multi-tenant workloads on BigQuery - common patterns used in multi-tenant data platforms. These patterns include ensuring reliability and isolation for customers of software as a service (SaaS) vendors, important BigQuery quotas and limits for capacity planning, using BigQuery Data Transfer Service to copy relevant datasets into another region, and more.
  • Use Materialized Views - how to use BigQuery Materialized Views for faster queries at lower cost, including querying materialized views, aligning partitions, and understanding smart-tuning (automatic rewriting of queries).