Specialization in Amazon Aurora

Increase Your Database Availability

RDS MySQL offers Multi-AZ configuration as a fault-tolerance strategy and allows adding read replicas. However, the Multi-AZ instance is not usable, and replication time between the source and replicas is often high, inhibiting its effectiveness in some scenarios.

With Amazon Aurora, when you create a Cluster, a high-performance, highly available managed storage service is created, shared among all read replicas, enabling synchronization with very low latency.

In the event of an original instance failure, a replica will be automatically promoted to a new original instance, restoring processing in a short time.

Distribute Your Multi-Tenant Application's Load

SaaS applications often use Multi-Tenant databases, where a single database serves multiple clients, making database scalability complex but essential when service usage increases.

With Amazon Aurora, you can configure a Cluster with multiple Write/Read instances, increasing application availability and computing power.

In case of an instance failure, any other instance can continue processing.

SaaS applications configured to use Amazon Aurora Multi-Master can employ custom load balancing strategies, prioritizing client traffic to specific instances.

Accelerate Analytical Reporting

Amazon Aurora executes analytical queries using the Parallel Query option, allowing queries to be run directly on the Cluster Storage, reducing execution time.

It also improves the execution of transactional operations and analytical queries.

Reduce Database Change Risks (Fast DB Clone)

Test structural changes or database cleanups using a clone of the production database.

With fast database cloning, you can create databases sharing the same data as the original database.

When testing the cloned database, only blocks related to changed data will occupy new storage space.

Quickly Recover to a Previous State

Occasionally, despite taking all precautions, the worst can happen, such as the deletion of an important table or unintentional data changes during maintenance.

With the Backtracking feature, you can return the database to a previous state and recover deleted data.

In the scenario below, the ITEM table is deleted at 10:30:15, and the database returns to the previous state at 10:35:20.

The backtracking option must be configured to enable its use.

Dynamically Scale Capacity to Meet Demand

In a traditional database, capacity is often provisioned to handle peak usage, leading to idle times and waste.

With Amazon Aurora, you can configure smaller instances, allowing for increased fault tolerance strategies.

When the number of users increases, in the previous scenario, users may already experience performance loss, while Amazon Aurora can add extra capacity to handle the demand.

In the previous scenario, if the number of users continues to increase, users start to experience widespread application processing failures, potentially resulting in revenue loss. Amazon Aurora continues to scale to accommodate additional demand.