Struggling to choose between Amazon Aurora and Amazon RDS? Both are robust AWS database solutions, but understanding their key differences is crucial for selecting the best AWS database solution for your needs. This guide provides a detailed comparison.
What is Amazon RDS?
Amazon Relational Database Service (RDS) simplifies running relational databases in the AWS cloud. Imagine a restaurant: you choose a dish (database engine) from the menu – MySQL, PostgreSQL, MariaDB, Oracle, Microsoft SQL Server, or Db2 – and the restaurant (RDS) handles the cooking and serving (database management).
You select your engine and instance size (determining CPU, memory, and storage), and RDS takes care of the rest. This includes database setup, patching, automated backups (with point-in-time recovery), and automatic failover options.
For high availability, Multi-AZ deployments replicate your data to a standby instance in another Availability Zone, ensuring minimal downtime if the primary instance fails. RDS also provides robust data security features, including rest and transit encryption. You control your data and schema; RDS configures physical hardware and routine database tasks.
You may also be interested in: Multi-Cloud storage: Definition and benefits
What is Amazon Aurora?
Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud by AWS and designed to achieve unmatched database performance and availability. If RDS is a versatile restaurant, Aurora is a Michelin-star chef specializing in MySQL and PostgreSQL. This chef (Aurora) uses superior ingredients (a custom, fast-distributed storage system) and innovative techniques to deliver exceptional results.
This translates to up to 5x the throughput of standard MySQL and 3x that of standard PostgreSQL. Aurora’s high-performance storage subsystem is a key differentiator. Your data is replicated across six storage nodes in three Availability Zones, providing exceptional durability and availability. The Aurora cluster volume scales automatically up to 128 TiB.
For read-heavy workloads, Aurora offers up to 15 low-latency Aurora Replicas. These replicas share the underlying storage, minimizing lag. Automatic failover to a replica typically happens within seconds. Aurora Global Database provides data replication across regions for disaster recovery, and Aurora Serverless offers on-demand scaling for unpredictable workloads. You can even rewind your Aurora database with the Backtrack feature.
Source: Statista.com
What are the architecture differences between Amazon Aurora and RDS?
The core architectural distinctions between Aurora and RDS stem from their underlying storage and replication mechanisms, impacting performance, availability, and scalability. Here’s a direct comparison:
| Feature | Amazon RDS | Amazon Aurora |
| Storage System | Amazon Elastic Block Storage (EBS) volumes. You choose volume type (General Purpose SSD, Provisioned IOPS SSD, Magnetic) and size. | Custom, distributed storage system designed for database workloads. Data replicated across six storage nodes in three Availability Zones. |
| Storage Scaling | Manual scaling (you must modify the instance and choose a larger EBS volume). | Automatic scaling up to 128 TiB. You don’t manage individual storage nodes. |
| Replication | Multi-AZ deployments (synchronous replication to a standby for high availability). Read Replicas (asynchronous replication for read scaling). | Storage-level replication (inherently distributed and highly available). Up to 15 low-latency Aurora Replicas that share storage with the primary, minimizing lag. Global Database option. |
| High Availability | Multi-AZ provides automatic failover to a standby instance (but the standby is not used for reads). | Automatic failover to an Aurora Replica (typically within seconds). Highly fault-tolerant storage system. |
| Backup & Restore | Automated backups to Amazon S3. Point-in-time recovery. Restoring creates a new DB instance. | Continuous backups to Amazon S3. Point-in-time recovery (1-second granularity). “Backtrack” feature. Faster restores due to shared storage. |
Aurora’s architecture is designed for high performance, high availability, and scalability from the ground up. While providing a managed database service, RDS uses a more traditional architecture based on EBS volumes and traditional database replication mechanisms.
You may also be interested in: Mastering Cloud Development Security Practices V. 1
What are the feature differences?
Beyond the core architectural differences, Aurora and RDS differ in their specific features and capabilities. Depending on your application’s requirements, these differences can significantly impact your choice.
The following table provides a detailed comparison of key features, highlighting where Aurora and RDS diverge and where they offer similar functionality:
| Feature | Amazon RDS |
Amazon Aurora |
|
Engine Compatibility |
MySQL, PostgreSQL, MariaDB, Oracle, SQL Server, Db2 | MySQL and PostgreSQL compatible |
|
Performance |
Depends on instance type and EBS volume type. Can achieve good performance with Provisioned IOPS SSD. |
Up to 5x faster than standard MySQL, up to 3x faster than standard PostgreSQL. Optimized for high I/O workloads. |
| Storage | Uses EBS volumes. You choose volume type and size. |
Uses a custom, distributed storage system. Storage automatically scales up to 128 TiB. Data is replicated across 6 storage nodes in 3 Availability Zones. |
|
Replication |
Multi-AZ for high availability (synchronous replication to a standby). Read Replicas for read scaling (asynchronous replication). |
Storage-level replication. Up to 15 low-latency Aurora Replicas that share the same underlying storage. Aurora Global Database for cross-region replication. |
|
High Availability |
Multi-AZ deployments provide automatic failover to a standby instance. |
Automatic failover to an Aurora Replica (typically within seconds). Highly fault-tolerant storage system. |
|
Scalability |
Vertical scaling (changing instance type). Read scaling with Read Replicas. |
Vertical scaling (changing instance type). Read scaling with up to 15 Aurora Replicas. Aurora Serverless provides automatic scaling of compute capacity. |
|
Backup and Restore |
Automated backups to S3. Point-in-time recovery. Restoring creates a new DB instance. |
Continuous backups to S3. Point-in-time recovery with 1-second granularity. “Backtrack” feature for fast rewinding. Faster restore times due to shared storage. |
|
Pricing |
Pay for instance type, storage, I/O, and backup storage. |
Pay for instance type, storage, I/O, and backup storage. Generally higher per-hour instance costs than RDS, but can be more cost-effective for high-throughput workloads due to reduced I/O needs. |
|
Security |
Encryption at rest (KMS), encryption in transit (SSL/TLS), network isolation (VPC), IAM integration. |
Same as RDS, plus enhanced security due to the distributed storage architecture and tighter integration with other AWS services. |
|
Monitoring |
Amazon CloudWatch metrics, Enhanced Monitoring, Performance Insights. |
Same as RDS, plus additional Aurora-specific metrics (e.g., replica lag). |
|
Migration |
AWS Database Migration Service (DMS), native database tools. |
AWS Database Migration Service (DMS), native database tools, snapshot import from RDS MySQL. |
What are the similarities between Aurora vs RDS?
While Aurora and RDS have distinct strengths and architectural differences, it’s important to remember that they also share a common foundation as part of the Amazon Web Services ecosystem. This shared foundation provides several key similarities that make both attractive options for many use cases.
Most significantly, both Aurora and RDS are fully managed database services. AWS takes responsibility for the often tedious routine database tasks that can consume valuable time and resources. These include patching the operating system and database software, performing automated backups, and handling automatic failover in case of an instance failure. This managed aspect is a huge benefit, freeing you to focus on your application and data, not database administration.
Furthermore, both services are built upon the relational database model. This means you can use your existing SQL knowledge and tools, making migration and development more straightforward. There’s no need to learn an entirely new query language or paradigm.
As part of the AWS family, Aurora and RDS integrate seamlessly with other AWS services. You can leverage Identity and Access Management (IAM) for fine-grained access control, use CloudWatch for comprehensive monitoring, and isolate your databases within a Virtual Private Cloud (VPC) for enhanced network security. This tight integration simplifies your overall cloud architecture.
Speaking of security, both services provide robust data security features. You get encryption at rest to protect your data on disk and encryption in transit to secure data as it moves between your application and the database. This helps ensure the confidentiality and integrity of your information, and you can use the AWS key management service to have complete control over it. Both services present high-availability solutions, such as multi-AZ deployments, to minimize downtime.
Finally, both Aurora and RDS are designed for ease of use. Whether you prefer the visual AWS Management Console, the command-line interface (CLI), or software development kits (SDKs), setting up and managing your databases is straightforward. This lowers the barrier to entry and allows you to get up and running quickly. Despite their differing performance and architectural characteristics, both services offer the core benefits of a managed relational database within the AWS ecosystem.
Choosing between Aurora and RDS depends on your workload requirements, performance needs, and budget. RDS is an excellent general-purpose relational database service, while Aurora is optimized for high performance, availability, and scalability.
We have extensive experience helping businesses choose and implement the right AWS database solution in Ceiba. Contact us today to discuss your needs and learn how we can help you build a robust and cost-effective database infrastructure.
You may also be interested in: Cloud Computing: Transforming the Banking Industry
