Your company is launching a new global inventory microservice that must record stock changes from data centers in North America, Europe, and Asia. The service requires a relational schema, strong ACID transactions across regions, and the ability to scale to thousands of writes per second without manual sharding or capacity management. Which managed Google Cloud data product best satisfies these requirements?
Spanner in a multi-region configuration to host the inventory tables
Bigtable with a product-ID-based row key and timestamp suffix
Cloud SQL for PostgreSQL with cross-region read replicas and promotion on failure
BigQuery with a partitioned table storing inventory mutations
Spanner is a fully managed, horizontally scalable relational database that offers global distribution with strong consistency and automatic sharding. Multi-region Spanner instances provide synchronous replication and single-row ACID transactions that can be committed from any region, meeting the requirement for consistent writes from multiple continents.
Cloud SQL can add cross-region read replicas, but only the primary instance accepts writes, so it cannot provide multi-master write scalability. Bigtable is a wide-column NoSQL store that lacks relational schemas and ACID transactions. BigQuery is an analytic data warehouse optimized for large queries, not for high-rate transactional updates. Therefore Spanner is the only option that meets all stated needs.
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