AWS RDS vs Aurora: Which Database Should You Choose?
Choosing the right cloud database is a critical decision that affects application performance, scalability, reliability, and cost. Amazon Web Services offers two key managed relational database options: Amazon RDS and Amazon Aurora. While both are part of the same RDS ecosystem, they differ significantly in architecture, performance, and pricing.
This guide provides a clear comparison to help you decide whether to use AWS RDS or Aurora for your next application.
What is AWS RDS?
AWS Relational Database Service (RDS) is a fully managed service that simplifies deploying, operating, and scaling relational databases in the cloud.
Supported Engines
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MySQL
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PostgreSQL
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MariaDB
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Oracle
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SQL Server
Key Features
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Automated backups and patching
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Multi-AZ high availability
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Read replicas (varies by engine)
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Up to 64 TB storage depending on engine
RDS is ideal for traditional enterprise workloads that require standard database engines and predictable performance.
What is Amazon Aurora?
Amazon Aurora is a high-performance, cloud-optimized relational database built by AWS for MySQL and PostgreSQL compatibility. It is not a database engine ported to the cloud, but a re-engineered version with a distributed storage architecture.
Supported Engines
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Aurora MySQL-Compatible
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Aurora PostgreSQL-Compatible
Key Features
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Up to 5x faster than MySQL and 3x faster than PostgreSQL
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Distributed, fault-tolerant storage
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Auto-scaling storage up to 128 TB
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Up to 15 low-latency read replicas
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Serverless and Global Database options
Aurora is built for mission-critical, highly scalable applications needing superior performance.
Architecture Comparison
| Feature | RDS | Aurora |
|---|---|---|
| Storage Architecture | Attached to instance | Shared distributed storage layer |
| Replication | Engine-specific | Built-in 6-copy replication across 3 AZs |
| Failover Time | ~60–120 seconds | < 30 seconds |
| Backup | Automated snapshots | Continuous + point-in-time recovery |
| Read Replicas | Up to 5 | Up to 15 |
Aurora’s architecture is superior for performance and fault tolerance due to its shared storage layer and automatic replication.
Performance Comparison
| Metric | RDS | Aurora |
|---|---|---|
| MySQL Performance | Baseline | Up to 5x faster |
| PostgreSQL Performance | Baseline | Up to 3x faster |
| Read Latency | Higher | Very low |
| Replication Lag | Possible | Almost zero |
Aurora is designed for high-performance workloads with large read/write demand.
Scalability
| Aspect | RDS | Aurora |
|---|---|---|
| Storage Scaling | Manual or autoscaling (limited) | Auto-scales up to 128 TB |
| Read Scaling | Limited replicas | Up to 15 replicas |
| Compute Scaling | Manual | Serverless v2 auto-scaling available |
Aurora offers significantly better auto-scaling, especially with Aurora Serverless v2.
High Availability and Durability
Both RDS and Aurora offer Multi-AZ, but Aurora provides stronger resilience.
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RDS Multi-AZ keeps one standby instance.
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Aurora stores six copies across three AZs and auto-heals faults.
Aurora Global Database also enables cross-region disaster recovery with sub-second replication, ideal for global applications.
Cost Comparison
Pricing varies based on engine, storage, and replica usage. Aurora costs more but provides higher performance.
General Cost Trends
| Category | RDS | Aurora |
|---|---|---|
| Instance Cost | Lower | Higher |
| Storage Cost | Lower | Higher (IO-based pricing) |
| Performance per Dollar | Good | Higher efficiency for heavy workloads |
RDS is cheaper for small to medium workloads.
Aurora is more cost-efficient for large, high-traffic production systems due to performance per node.
When to Choose AWS RDS
Choose RDS when:
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You need a traditional relational database with minimal changes
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Your workload is moderate with predictable queries
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You need Oracle or SQL Server (Aurora does not support them)
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Budget is limited and performance needs are average
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You want full engine compatibility for legacy apps
Common Use Cases
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Small to medium-scale web apps
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ERP, CRM, and enterprise applications
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On-prem database migrations with minimal refactoring
When to Choose Amazon Aurora
Choose Aurora when:
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You need high throughput and low latency
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Your application requires automatic scaling
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You want high availability and global replication
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You run SaaS, gaming, finance, eCommerce, or analytics-heavy apps
Common Use Cases
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Large-scale web and mobile applications
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High-traffic SaaS platforms
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Fintech and real-time systems
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Global multi-region applications
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Microservices and event-driven architectures
Aurora Serverless vs RDS
Aurora Serverless offers on-demand auto-scaling compute capacity. It is ideal for variable workloads.
| Feature | RDS | Aurora Serverless |
|---|---|---|
| Scaling | Manual | Auto |
| Best for | Steady workloads | Sporadic or unpredictable workloads |
If your workload is unpredictable, Aurora Serverless is a strong cost-efficient option.
Final Decision Guide
| If you need | Choose |
|---|---|
| Lowest cost and simplicity | RDS |
| High-performance cloud-native DB | Aurora |
| Full engine compatibility | RDS |
| Global low-latency reads | Aurora |
| SQL Server or Oracle | RDS |
| Auto-scaling with serverless | Aurora |
Conclusion
Both AWS RDS and Amazon Aurora offer reliable, managed relational database solutions, but they serve different needs. RDS is the right choice for traditional workloads, cost-sensitive environments, and full compatibility across multiple engines. Aurora is ideal for high-performance, highly scalable, global applications looking to leverage cloud-native database innovation.
If budget is a priority and workloads are moderate, go with RDS. If performance, scalability, and reliability are critical to your business, Aurora is the clear winner.
