Your ecommerce platform runs a self-managed PostgreSQL 12 cluster handling 25 000 write TPS against 10 TB of data. Business analysts need sub-second ad-hoc reporting on the same tables without affecting OLTP latency. You must lift-and-shift to Google Cloud within one quarter, reuse existing SQL, avoid managing storage-compute scaling or patching, and minimize downtime during future maintenance. Which managed Google Cloud service best satisfies both transactional and analytical requirements while preserving PostgreSQL compatibility?
Cloud SQL for PostgreSQL with high-availability configuration and read replicas
Spanner configured with the PostgreSQL interface
BigQuery with federated external tables over exported data
AlloyDB for PostgreSQL is a fully managed, PostgreSQL-compatible service that separates compute and log-structured storage to deliver high write throughput and near-linear read scaling through read pools. It offers an integrated columnar engine that accelerates analytical queries by orders of magnitude on the same operational data, and Google handles replication, patching, and zero-downtime maintenance. Cloud SQL provides PostgreSQL compatibility but lacks the columnar accelerator and can suffer from replication lag under heavy write loads. Spanner's PostgreSQL interface is not identical to upstream PostgreSQL and would require more re-engineering, while BigQuery excels at analytics but is not suitable for high-write OLTP workloads and would force a dual-system architecture.
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