AWS Aurora vs RDS: Top Considerations & Tradeoffs for 2023
Amazon Web Services (AWS) offers two managed database services: Amazon RDS and Amazon Aurora. Both services provide a scalable, reliable, and cost-effective solution for managing relational databases in the cloud. In this article, we’ll compare the pros and cons of AWS Aurora and RDS, considering features, pricing, ecosystem, community, support, scalability, architecture, replication, failover, resiliency, and other relevant factors for DevOps engineers.
AWS Aurora Features
Aurora is a fully managed, MySQL and PostgreSQL-compatible relational database engine. It’s designed to deliver up to five times the performance of MySQL and three times the performance of PostgreSQL. Key features include:
- automatic storage scaling
- high availability with up to 15 read replicas
- continuous backup to Amazon S3
- fast database cloning
- backtrack for rewinding the database to a previous point in time
- serverless mode for on-demand capacity
- global database for cross-region replication
AWS RDS Features
RDS is a managed relational database service that supports six database engines: MySQL, PostgreSQL, MariaDB, Oracle, Microsoft SQL Server, and Amazon Aurora. Key features include:
- automatic backups
- Multi-AZ deployments for high availability
- read replicas for read-heavy workloads
- database snapshots
- automatic host replacement
- monitoring and performance insights
AWS Aurora Pricing
Aurora pricing is based on the instance class, storage, I/O, and backup storage. There are two pricing models: On-Demand and Reserved Instances. On-Demand pricing allows you to pay for capacity as you need it, while Reserved Instances offer significant discounts for long-term commitments.
AWS RDS Pricing
RDS pricing depends on the database engine, instance class, storage, I/O, and backup storage. Similar to Aurora, RDS offers On-Demand and Reserved Instances pricing models.
AWS Aurora Ecosystem and Community
Aurora is an AWS-native service, which means it’s tightly integrated with other AWS services like Lambda, CloudWatch, and CloudFormation. The community around Aurora is growing, with numerous blog posts, tutorials, and case studies available.
AWS RDS Ecosystem and Community
RDS supports multiple database engines, which means it benefits from the larger community and ecosystem around each engine. RDS also integrates well with other AWS services.
Support
Both Aurora and RDS are fully managed services, which means AWS handles the underlying infrastructure, patching, backups, and monitoring. AWS provides support through various channels, including documentation, forums, and paid support plans.
Scalability and Architecture: AWS Aurora
Aurora is designed for high scalability, with automatic storage scaling up to 128 TB and support for up to 15 read replicas. Aurora also offers a serverless mode, which automatically adjusts capacity based on workload.
Scalability and Architecture: AWS RDS
RDS provides vertical scaling by changing the instance class and horizontal scaling with read replicas. However, RDS doesn’t offer automatic storage scaling or serverless mode like Aurora.
Replication: AWS Aurora
Aurora supports up to 15 read replicas, with sub-10ms replica lag. Aurora Global Database enables cross-region replication for disaster recovery and low-latency global reads.
Replication: AWS RDS
RDS supports read replicas for MySQL, PostgreSQL, and MariaDB, with a maximum of five replicas. Cross-region replication is available for MySQL and PostgreSQL.
Failover and Resiliency: AWS Aurora
Aurora provides automatic failover with Multi-AZ deployments and read replicas. Aurora also offers backtrack, which allows you to rewind the database to a previous point in time without restoring from a backup.
Failover and Resiliency: AWS RDS
RDS supports automatic failover with Multi-AZ deployments. However, RDS does not offer a backtrack feature like Aurora.
Conclusion
AWS Aurora and RDS both offer robust managed database solutions with trade-offs that need to be carefully weighed for each specific use case.