AWS Database Showdown: Amazon Aurora vs. Amazon RDS

Core Concepts

What is Amazon RDS?

Amazon Relational Database Service (RDS) is a managed database service that simplifies the setup, operation, and scaling of relational databases in the cloud. It provides a selection of popular database engines and manages common administration tasks like patching, backups, and high availability. With RDS, you choose a specific database engine (like MySQL, PostgreSQL, etc.) and manage it on a provisioned EC2-like instance, though the underlying instance is managed by AWS.

What is Amazon Aurora?

Amazon Aurora is a cloud-native relational database built by AWS, fully compatible with MySQL and PostgreSQL. It's not just a managed version of these engines; it's a re-architected database designed for the cloud. Aurora separates compute and storage, featuring a unique, log-structured, distributed storage system. This architecture provides superior performance, scalability, and availability compared to traditional monolithic databases running on RDS. Aurora is a specific engine option within the Amazon RDS service.

Head-to-Head Comparison: Aurora vs. RDS

1. Architecture & Storage

• Amazon RDS:

  • Uses a traditional, monolithic architecture. The database engine, processing, and storage are all tightly coupled on a single provisioned EC2 instance.
  • Storage is typically on an Amazon Elastic Block Store (EBS) volume attached to the instance.
  • For High Availability (Multi-AZ), RDS maintains a full, synchronous, block-level replica of the entire database instance in a separate Availability Zone (AZ).

• Amazon Aurora:

  • Features a decoupled, service-oriented architecture. The compute layer (handling queries) is separate from the storage layer.
  • The storage layer is a unique, distributed, and self-healing system.
  • A single database volume is replicated 6 times across 3 Availability Zones.
  • Writes are sent to all 6 storage nodes, and a write is acknowledged once a quorum of 4 out of 6 nodes confirms it. This makes writes extremely durable and fast.

2. Performance

• Amazon RDS:

  • Performance is tied to the chosen instance type and the EBS volume type (gp2, gp3, io1, io2). Performance can be excellent but is limited by the single-instance architecture.
  • Write performance in Multi-AZ mode is impacted by the synchronous replication to the standby instance.

• Amazon Aurora:

  • Up to 5x faster than standard MySQL on RDS and up to 3x faster than standard PostgreSQL on RDS.
  • The distributed, log-structured storage system minimizes I/O operations, significantly boosting throughput for both reads and writes.
  • Writes are offloaded to the storage layer, freeing up the compute instance for query processing.

3. High Availability & Durability

• Amazon RDS (Multi-AZ):

  • Provides high availability via a standby instance in a different AZ.
  • In case of a primary instance failure, RDS performs an automatic failover to the standby instance. This involves a DNS change.
  • Failover time: Typically 1-2 minutes. There is a brief downtime.
  • Data is synchronously replicated, so there is no data loss.

• Amazon Aurora:

  • Built-in fault tolerance. With 6 copies of data, it can tolerate the loss of an entire AZ plus one additional storage node without any impact on write availability, and the loss of an AZ without impact on read availability.
  • Failover is much faster. If the primary DB instance fails, Aurora automatically promotes one of the up to 15 Read Replicas to be the new primary.
  • Failover time: Typically under 30 seconds.
  • Aurora Global Database: Provides disaster recovery by replicating the database across multiple AWS Regions with a typical lag of under 1 second. A region-level failover can complete in less than a minute.

4. Scalability & Read Replicas

• Amazon RDS:

  • Supports up to 5 Read Replicas.
  • Replication is asynchronous. A dedicated replication process is used, which can add load to the primary instance.
  • Each replica has its own storage volume, and you pay for both the compute and storage for each replica.

• Amazon Aurora:

  • Supports up to 15 Read Replicas.
  • Replicas share the same underlying storage volume as the primary instance. This is a key advantage.
  • Replication lag is typically much lower (often under 10ms) because there's no need to replay transaction logs on the replica; they just read from the shared volume.
  • Since storage is shared, creating a replica is extremely fast. You only pay for the replica's compute instance.

5. Database Engine Support

• Amazon RDS:

  • Supports a wide range of engines:
    • MySQL
    • PostgreSQL
    • MariaDB
    • Microsoft SQL Server
    • Oracle

• Amazon Aurora:

  • A specific engine type, not a collection. It offers two compatibility modes:
    • Aurora MySQL (compatible with MySQL)
    • Aurora PostgreSQL (compatible with PostgreSQL)

6. Backup & Restore

• Amazon RDS:

  • Provides automated daily snapshots and allows for manual snapshots.
  • Backups are stored in Amazon S3.
  • A restore operation creates a completely new RDS instance from the snapshot, which can be time-consuming.

• Amazon Aurora:

  • Features continuous, incremental backups to S3 with no performance impact on the database.
  • Supports Point-in-Time Recovery (PITR) down to the second within your backup retention period.
  • Includes a "Backtrack" feature (for Aurora MySQL only) that allows you to "rewind" your database cluster to a specific point in time without restoring from a backup. This is extremely fast (takes minutes).

7. Pricing Model

• Amazon RDS:

  • You pay for the DB instance hours, provisioned storage (EBS), and data transfer.
  • In a Multi-AZ setup, you pay for both the primary and standby instances.

• Amazon Aurora:

  • You pay for the DB instance hours.
  • Storage is billed based on actual usage (pay-per-GB) and I/O operations. You don't provision storage in advance.
  • You are not billed for storage on the Read Replicas, only for their instance hours.
  • Can be more cost-effective for I/O-intensive workloads, but the I/O charges can make it more expensive for low-traffic applications.

Summary Table: Aurora vs. RDS

Decision Guide: When to Use Which?

Choose Amazon RDS when:

• You need a database engine other than MySQL or PostgreSQL (e.g., SQL Server, Oracle, MariaDB).
• You have a small-scale or low-traffic application (like a dev/test environment or a small blog) where Aurora's performance and I/O costs might be overkill.
• You want a simple, predictable pricing model based on instance hours and provisioned storage.
• You are migrating an existing application that has specific dependencies on a standard engine version not yet supported by Aurora.

Choose Amazon Aurora when:

• You require high throughput, low latency, and high availability for mission-critical applications.
• Your application is I/O-intensive and would benefit from Aurora's advanced storage architecture.
• You need more than 5 Read Replicas or want extremely low replication lag.
• Fast failover times (< 30 seconds) are a critical business requirement.
• You want to leverage advanced features like Global Database for disaster recovery or Aurora Serverless v2 for highly variable workloads.
• Your primary concern is performance and scalability over a slightly more complex pricing model.