RDS vs Cloud SQL vs Azure SQL

Amazon RDS, Google Cloud SQL, and Azure SQL Database are the managed relational database services from the three major cloud providers. All handle backups, patching, replication, and failover so your team can focus on application logic instead of database administration.

Engine Support

RDS offers the broadest selection: MySQL, PostgreSQL, MariaDB, Oracle, SQL Server, and Amazon Aurora (MySQL and PostgreSQL compatible). Cloud SQL supports MySQL, PostgreSQL, and SQL Server. Azure SQL Database focuses on SQL Server compatibility with Azure SQL Managed Instance for full SQL Server feature parity.

Aurora is Amazon's differentiator — a MySQL/PostgreSQL-compatible engine redesigned for the cloud with up to 5x better performance than standard MySQL and 3x better than standard PostgreSQL, with storage that automatically scales to 128 TB.

Scaling Options

Aurora Serverless v2 automatically scales compute capacity based on demand, scaling to zero when idle. This is unique among the three providers. Cloud SQL and Azure SQL Database require choosing an instance size and manually scaling (or using scheduled scaling).

For read scaling, Aurora supports up to 15 read replicas with sub-100ms replication lag. Cloud SQL supports 10 read replicas. Azure SQL supports readable secondaries via geo-replication.

Pricing Comparison

RDS pricing is complex: instance hours + storage + provisioned IOPS (for io1/io2) + data transfer. Cloud SQL includes I/O in the base price, making cost estimation simpler. Azure SQL Database offers DTU-based and vCore-based pricing models.

For small databases, Cloud SQL's included I/O often makes it cheaper. For large, I/O-intensive workloads, RDS with Aurora's optimized storage engine may deliver better price-performance.

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