Cost effective

Moving to AWS managed databases eliminates multiple cost categories: such as hardware procurement and refresh cycles, data center facilities and power, operating system and database licensing, administrative overhead, and backup infrastructure. While traditional high availability solutions often double infrastructure costs, AWS architecture provides resilience more efficiently. Multi-AZ deployments maintain standby resources with optimized storage replication, while read replicas serve production traffic to maximize resource utilization. To illustrate, organizations who adopted Aurora realized a 42% lower TCO, 6 months payback on investment, and 434% three-year ROI. Likewise, organizations who adopted DynamoDB realized a 25% lower TCO, 8 months payback on investment, and 378% three-year ROI.

Database choice also significantly impacts your total costs. For example, data that can be associated with a unique key, such as customer name, user profile, or simple configurations, are ideal for a key-value database and can reduce costs as compared to using a traditional relational database. Often the first step to cost optimization starts with choosing the right database for your workload. As your applications grow, built-in scaling capabilities ensure costs remain aligned with actual usage rather than provisional capacity.

AWS engineers are also innovating to improve operational efficiencies, and we pass those efficiencies back to customers as cost reductions. DynamoDB's on-demand pricing has recently been reduced by up to 50% and global tables by up to 67%, making it more cost-effective than ever to build fully serverless applications. Your database automatically scales to handle any level of traffic and scales down to zero when idle,  and you pay only for the actual reads and writes performed. Likewise, Amazon ElastiCache Serverless for Valkey is priced 33% lower than ElastiCache Serverless for Redis OSS –you can create a cache in under a minute priced as low as $6 per month.

Serverless databases dramatically reduce waste from overprovisioning. Amazon Aurora DSQL automatically scales both vertically and horizontally to match your application's demands, charging only for resources used. During low-traffic periods, such as nights and weekends, capacity adjusts automatically to actual usage, significantly reducing costs for development and test environments. This true serverless architecture ensures you only pay for the compute and storage resources your applications consume, eliminating the need to provision for peak capacity.

For customers who need price predictability for I/O-intensive workloads, AWS offers I/O-Optimized pricing for Aurora, DocumentDB, and Neptune. You only pay for your database instances and storage usage, and there are zero charges for read and write I/O operations. I/O-Optimized gives you predictable pricing for all applications regardless of evolving data access patterns or I/O usage. It eliminates variability in I/O spend.

AWS Graviton4 processors deliver superior price-performance for database workloads. On Amazon Aurora and RDS, Graviton4-based instances provide up to a 40% performance improvement and up to 29% price/performance improvement for on-demand pricing over Graviton3-based instances.

Amazon RDS io2 Block Express volumes are designed for I/O-intensive, mission-critical database workloads that demand high performance, high throughput, and sub-millisecond latency. io2 Block Express storage has the lowest p99.9 I/O latency and the best outlier latency control among major cloud providers. It supports 99.999% durability, up to 64 TiB volumes, 4,000 MB/s throughput, up to 256,000 Provisioned IOPS, and 20x more IOPS/GiB from provisioned storage – all at the same price as RDS io1 volumes. Upgrading to io2 Block Express volumes requires zero downtime and zero additional storage cost.

The RDS for Oracle and RDS for SQL Server Optimize CPU feature lets you customize CPU resources for your workload, potentially reducing license costs for database engines with CPU-based licensing. By matching CPU allocation to your actual needs, you can significantly reduce licensing expenses while maintaining performance. From licensing to infrastructure, AWS is focused on driving down the costs for running SQL Server workloads. For example, customers save an average of 45% on SQL Server license costs through the free AWS Optimization and Licensing Assessment. With AWS Compute Optimizer, customers save up to 25% on infrastructure through rightsizing and up to 73% on licenses through SQL Server edition downgrading recommendations.

Development environments benefit from several cost-saving features:

• Free tier access for testing and prototyping
• DynamoDB and Aurora Serverless scale down to zero during idle periods
• Database cloning without additional storage costs
• Development endpoints that run only when needed