Your team is re-architecting the core reservation system for a global airline running on Google Cloud. The application must store highly structured booking data and let microservices in multiple regions perform thousands of multi-row updates per second while guaranteeing ACID transactions and strong global consistency. Schema evolution must be online, and the database has to scale horizontally with minimal operational overhead. Which managed storage service best meets these requirements?
Store bookings in BigQuery partitioned tables with streaming inserts.
Use a multi-region deployment of Cloud Spanner.
Deploy Cloud SQL for PostgreSQL with cross-region read replicas.
Use Cloud Bigtable with multi-cluster routing and export data to BigQuery for analytics.
Cloud Spanner is designed for globally distributed OLTP workloads that need relational semantics, strong consistency, and horizontal scale. A multi-region Spanner instance synchronously replicates data across regions, supports ANSI SQL, multi-row commits, and online schema changes with no downtime. Cloud SQL only allows one writable primary per instance; cross-region replicas are read-only, so it cannot provide globally consistent writes or unlimited scale. BigQuery is optimized for analytical queries and is not intended for high-rate transactional updates. Cloud Bigtable offers massive scalability but lacks SQL joins, foreign keys, and strong cross-region consistency, so it cannot satisfy the ACID and relational requirements.
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What is ACID in databases?
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