Amazon Aurora provides built-in replication as part of its Aurora DB Cluster architecture, which is different from Aurora Read Replicas in terms of how they are implemented and used.
Let’s break down the differences between Aurora DB Cluster built-in replication and Aurora Read Replicas:
1. Aurora DB Cluster Built-in Replication
- Replication Model: Aurora DB Cluster uses a shared storage model with built-in replication. This means that all instances in an Aurora cluster (primary and read replicas) share the same underlying storage volume, and data is automatically replicated across multiple Availability Zones (AZs) in real-time.
- Data Availability: Aurora’s storage is distributed across multiple AZs, and the data is automatically replicated across these AZs. The primary instance and read replicas all access this shared, fault-tolerant storage.
- Fault Tolerance: Aurora’s architecture automatically handles failures. If the primary instance fails, Aurora automatically promotes one of the read replicas to become the new primary instance. This failover mechanism happens without manual intervention.
- Consistency: Aurora DB Cluster provides strong consistency because all instances read from the same shared storage, and data is synchronized in real-time.
Key Benefits of Aurora DB Cluster Built-in Replication:
- Highly available with data automatically replicated across multiple AZs.
- Automatic failover from the primary instance to a replica in case of failure.
- No manual setup for replication — it’s part of the cluster’s design.
- Single storage layer shared across all instances, providing efficient scaling.
2. Aurora Read Replicas
- Replication Model: Aurora Read Replicas are separate instances that are created within an Aurora DB Cluster to offload read traffic from the primary instance. These replicas replicate data from the primary instance asynchronously.
- Asynchronous Replication: Aurora Read Replicas use asynchronous replication to keep the data in sync with the primary instance. This means there can be some replication lag, and read replicas may not reflect the latest data immediately after a write operation on the primary instance.
- Read-only: Aurora Read Replicas are read-only. They can be used to serve read-heavy workloads (e.g., reporting, analytics) to reduce the load on the primary instance.
- Manual Failover: If you want to use an Aurora Read Replica as the primary instance, you can manually promote it to become the primary instance. However, this is a manual process and does not occur automatically like the failover in the Aurora DB Cluster.
Key Benefits of Aurora Read Replicas:
- Offload read traffic from the primary instance to improve application performance.
- Scalable: You can add up to 15 read replicas to a cluster to handle read-heavy workloads.
- Geographically distributed: You can create read replicas in different AWS regions to serve global users (with Aurora Global Databases).
- Cost-effective: You only pay for the read replicas you create, providing a way to scale out reads without needing to scale up the primary instance.
Comparison: Aurora DB Cluster Built-in Replication vs Aurora Read Replicas
| Feature | Aurora DB Cluster Built-in Replication | Aurora Read Replicas |
|---|---|---|
| Replication Type | Synchronous replication across multiple AZs. | Asynchronous replication from the primary instance to read replicas. |
| Write Operations | The primary instance handles writes, with data replicated to other instances. | Read replicas do not handle write operations; they only handle read traffic. |
| Availability | High availability with automatic failover from primary to replica in case of failure. | Manual failover (manual promotion) required if you want a read replica to become the primary. |
| Failover | Automatic failover to a read replica if the primary instance fails. | Manual failover needed to promote a read replica to primary. |
| Use Case | Fault tolerance, high availability, and scaling of both reads and writes within a single cluster. | Read scaling and offloading read traffic from the primary instance to serve read-heavy workloads. |
| Instance Storage | Shared storage across all instances in the cluster. | Separate instances with replication lag (read replicas are not always up-to-date). |
| Consistency | Strong consistency across all instances in the cluster. | Eventual consistency (due to asynchronous replication), meaning replicas might be behind the primary instance. |
| Scaling | Horizontal scaling through read replicas and vertical scaling of the primary instance. | Horizontal scaling by adding read replicas (up to 15), only for read traffic. |
| Maximum Number of Replicas | Multiple read replicas, but no upper limit on the number of replicas in the same region. | Up to 15 read replicas can be added to a cluster. |
When to Use Aurora DB Cluster Built-in Replication vs Aurora Read Replicas
- Use Aurora DB Cluster Built-in Replication if:
- You need high availability and automatic failover in case of primary instance failure.
- You want synchronous replication for consistent, up-to-date data across your instances.
- You need fault-tolerant, highly available architecture with automatic data replication across multiple Availability Zones.
- Use Aurora Read Replicas if:
- You need to offload read traffic from the primary instance to improve performance, especially for read-heavy workloads.
- You want to scale out reads horizontally by adding multiple read replicas to your cluster.
- You need low-cost scaling for read-heavy applications without the need for scaling the primary instance.
- You need cross-region replication for global applications (using Aurora Global Databases).
Amazon Aurora Database Cloning
Amazon Aurora Database Cloning is a feature that allows you to quickly create an exact copy of an existing Aurora database cluster. The cloned database is created with a low overhead and doesn’t require a full backup or restore process, making it ideal for scenarios like testing, development, and database troubleshooting.
Key Features of Aurora Database Cloning:
- Fast and Cost-Efficient:
- Aurora cloning is fast and uses minimal storage during the initial creation. The clone starts as a copy-on-write snapshot of the original database, which means that storage is only used for changes made to the cloned database.
- No need to wait for a full backup or restore process to complete. You can start working with the clone almost immediately.
- Independent Operations:
- Once created, the clone is fully independent of the source database. You can perform read/write operations on the clone without affecting the original database.
- Changes to the cloned database don’t impact the source, and vice versa.
- Low Overhead:
- Since the clone is based on a copy-on-write mechanism, it starts with shared storage and only uses additional storage for the changes made to the cloned database.
- Same Performance:
- The performance of the clone is identical to that of the source database, as it uses the same underlying Aurora architecture.
- Useful for Testing & Development:
- You can create a clone of the production database to test new features, run queries, or replicate specific use cases without affecting production workloads.
- It’s also useful for development teams to work with realistic data while ensuring that the production database remains untouched.
- Supports Aurora MySQL & Aurora PostgreSQL:
- Aurora database cloning is available for both Aurora MySQL and Aurora PostgreSQL databases.