Amazon Aurora MySQL PostgreSQL Features | Relational Database | AWS

Amazon Aurora is a relational database service that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases. Aurora is fully compatible with MySQL and PostgreSQL, allowing existing applications and tools to run without requiring modification.

High Performance and Scalability

Up to 5X the throughput of MySQL and 3X the throughput of PostgreSQL

Testing on standard benchmarks such as SysBench has shown an increase in throughput of up to 5X over stock MySQL and 3X over stock PostgreSQL on similar hardware. Amazon Aurora uses a variety of software and hardware techniques to ensure the database engine is able to fully use available compute, memory, and networking. I/O operations use distributed systems techniques, such as quorums to improve performance consistency.

Serverless Configuration

Amazon Aurora Serverless is an on-demand, auto-scaling configuration for Aurora where the database automatically starts up, shuts down, and scales capacity up or down based on your application’s needs. Run your database in the cloud without managing any database instances.

Push-Button Compute Scaling

You can use the Amazon Relational Database Service (Amazon RDS) APIs or the AWS Management Console to scale provisioned instances powering your deployment up or down. Compute scaling operations typically complete in a few minutes.

Storage Auto-Scaling

Amazon Aurora automatically increases the size of your database volume as your storage needs grow. Your volume expands in increments of 10 GB up to a maximum of 128 TB. You don’t need to provision excess storage for your database to handle future growth.

Low-Latency Read Replicas

You can increase read throughput to support high-volume application requests by creating up to 15 database Amazon Aurora Replicas. Aurora Replicas share the same underlying storage as the source instance, lowering costs and avoiding the need to perform writes at the replica nodes. This frees up more processing power to serve read requests and reduces the replica lag time—often down to single-digit milliseconds. Aurora provides a reader endpoint so the application can connect without having to keep track of replicas as they are added and removed. It also supports auto-scaling, automatically adding and removing replicas in response to changes in performance metrics that you specify.

Aurora supports cross-region read replicas. Cross-region replicas provide fast local reads to your users, and each region can have an additional 15 Aurora replicas to further scale local reads. See Amazon Aurora Global Database for details.

Custom Database Endpoints

Custom endpoints allow you to distribute and load balance workloads across different sets of database instances. For example, you can provision a set of Aurora Replicas to use an instance type with higher memory capacity in order to run an analytics workload. A custom endpoint can then help you route the workload to these appropriately configured instances while keeping other instances isolated from it.

Parallel Query for Aurora MySQL

Amazon Aurora Parallel Query provides faster analytical queries compared to your current data. It can speed up queries by up to two orders of magnitude while maintaining high throughput for your core transaction workload. By pushing query processing down to the Aurora storage layer, it gains a large amount of computing power while reducing network traffic. Use Parallel Query to run transactional and analytical workloads alongside each other in the same Aurora database. Parallel Query is available for Amazon Aurora with MySQL compatibility.

Diagnose and Resolve Performance Bottlenecks with Amazon DevOps Guru for RDS

Amazon DevOps Guru is a cloud operations service powered by machine learning (ML) that helps improve application availability. With Amazon DevOps Guru for RDS, you can use ML-powered insights to help easily detect and diagnose performance-related relational database issues and is designed to resolve them in minutes rather than days. Developers and DevOps Engineers can use DevOps Guru for RDS to automatically identify the root cause of performance issues and get intelligent recommendations to help address the issue, without needing help from database experts.

To get started, simply go to the Amazon RDS Management Console and enable Amazon RDS Performance Insights. Once Performance Insights is on, go to the Amazon DevOps Guru Console and enable it for your Amazon Aurora resources, other supported resources, or your entire account.