RDS vs Aurora: A Detailed Pricing Comparison

Amazon's Relational Database Service (RDS) and Amazon Aurora are two major database offerings from AWS, ranking high on the AWS Cost Leaderboard due to their extensive use. While both services cater to a variety of use cases, they differ in terms of performance, features, and pricing, influencing the choice between them. RDS, launched in 2009, supports multiple database engines and automates tasks like backups and scaling, while Aurora, introduced five years later, is cloud-optimized, offering high performance and scalability with separate compute and storage layers. Aurora's pricing model includes options like Standard and I/O-Optimized, with the latter designed for I/O-intensive applications, whereas RDS charges based on provisioned resources. Pricing factors such as region, database engine, and instance type can affect costs for both services. Although RDS is generally more cost-effective for moderate and predictable needs, Aurora's features may justify its higher costs for specific scenarios, particularly for I/O-intensive workloads or variable traffic patterns, where Aurora I/O-Optimized and Aurora Serverless options can offer savings.