RDS vs Aurora: Key Differences and When to Use Each

Amazon RDS is a managed relational database service supporting multiple engines, while Aurora is a high-performance, cloud-optimized database engine compatible with MySQL and PostgreSQL. Aurora offers better scalability and availability with faster replication and storage auto-scaling compared to standard RDS.

Quick Comparison

This table summarizes the main differences between Amazon RDS and Aurora.

Feature	Amazon RDS	Amazon Aurora
Database Engines	Supports MySQL, PostgreSQL, Oracle, SQL Server, MariaDB	Compatible with MySQL and PostgreSQL only
Performance	Standard performance based on chosen instance	Up to 5x faster than standard MySQL, 3x faster than standard PostgreSQL
Scalability	Manual scaling of instances and storage	Auto-scaling storage, up to 128 TB; supports read replicas with low latency
High Availability	Multi-AZ deployments with synchronous replication	Fault-tolerant distributed storage with automatic failover
Cost	Lower base cost, pay per instance and storage	Higher cost but includes performance and availability benefits
Storage	Fixed storage size, manual increase	Distributed, auto-scaling storage across multiple AZs

Key Differences

Amazon RDS is a managed service that lets you run popular database engines like MySQL, PostgreSQL, Oracle, and SQL Server with ease. You choose the instance size and storage, and AWS handles backups, patching, and failover. However, scaling and replication are more manual and can have higher latency.

Aurora is a cloud-native database engine built by AWS to improve performance and availability. It is compatible with MySQL and PostgreSQL but uses a distributed storage system that automatically scales and replicates data across multiple availability zones. This design reduces failover time and increases throughput, making it ideal for demanding applications.

In summary, RDS offers flexibility with multiple engines and simpler cost, while Aurora provides advanced performance, automatic scaling, and higher availability for cloud-optimized workloads.

Code Comparison

Here is an example of creating a MySQL database instance using AWS CLI for Amazon RDS.

bash

aws rds create-db-instance \
    --db-instance-identifier mydbinstance \
    --db-instance-class db.t3.medium \
    --engine mysql \
    --allocated-storage 20 \
    --master-username admin \
    --master-user-password MyPassword123 \
    --backup-retention-period 7 \
    --multi-az

Output

Creates a MySQL RDS instance named 'mydbinstance' with multi-AZ support and 20 GB storage.

Aurora Equivalent

Here is how to create an Amazon Aurora MySQL cluster using AWS CLI.

bash

aws rds create-db-cluster \
    --db-cluster-identifier myauroracluster \
    --engine aurora-mysql \
    --master-username admin \
    --master-user-password MyPassword123 \
    --backup-retention-period 7

Output

Creates an Aurora MySQL cluster named 'myauroracluster' with automated backups.

When to Use Which

Choose Amazon RDS when you need support for multiple database engines, have moderate performance needs, or want a simpler cost structure. It is great for traditional applications that do not require extreme scalability or ultra-low failover times.

Choose Amazon Aurora when you need high performance, automatic storage scaling, and high availability with minimal failover time. Aurora is ideal for cloud-native applications, large-scale web services, and workloads requiring fast replication and fault tolerance.

Key Takeaways

Amazon RDS supports multiple database engines; Aurora supports only MySQL and PostgreSQL compatible engines.

Aurora offers better performance and automatic storage scaling compared to standard RDS.

Aurora provides higher availability with distributed storage and faster failover.

Use RDS for simpler, cost-effective setups and Aurora for demanding, scalable cloud applications.