Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, which combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases.

Amazon Aurora is up to five times faster than standard MySQL database and thrice  faster than standard PostgreSQL database. It provides the security, availability, and reliability of commercial databases at 1/10th the cost. Amazon Aurora is fully managed by Amazon Relational database service (RDS), which automates time-consuming administration tasks like hardware provisioning, database setup, patching, and backups.

Amazon Aurora features a distributed, fault-tolerant, self-healing storage system that auto-scales up to 64TB per database instance. It delivers high performance and availability with up to 15 low-latency read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across three Availability Zones (AZs).

Benefits:

High Performance and Scalability

Get 5X the throughput of standard MySQL and 3X the throughput of standard PostgreSQL. This performance is at par with commercial databases, at 1/10th the cost.

High Availability and Durability

Amazon Aurora is designed to offer greater than 99.99% availability, replicating 6 copies of data across 3 Availability Zones and backing up data continuously to Amazon S3. It transparently recovers from physical storage failures; instance failover typically takes less than 30 seconds.

Highly Secure

Amazon Aurora as a database service provides multiple levels of security for your database. These include network isolation using Amazon VPC, encryption at rest using keys you create and control through AWS Key Management Service (KMS) and encryption of data in transit using SSL.

MySQL and PostgreSQL Compatible

The Amazon Aurora database engine is fully compatible with existing MySQL and PostgreSQL open source databases, and it adds compatibility for new releases regularly. This means you can easily migrate MySQL or PostgreSQL databases to Aurora using standard MySQL or PostgreSQL import/export tools or snapshots. It also means the code, applications, drivers, and tools you already use with your existing databases can be used with Amazon Aurora with little or no change.

Fully Managed

Amazon Aurora is fully managed by Amazon Relational Database Service (RDS). So no longer need to worry about database management tasks such as hardware provisioning, software patching, setup, configuration, or backups. It automatically and continuously monitors and backs up your database to Amazon S3, enabling granular point-in-time recovery. You can monitor database performance using Amazon CloudWatch, Enhanced Monitoring, or Performance Insights, an easy-to-use tool that helps you quickly detect performance problems.

Migration Support

MySQL and PostgreSQL compatibility make Amazon Aurora a compelling target for database migrations to the cloud. If you're migrating from MySQL or PostgreSQL, there are various  lists of tools and options from which you can manage. To migrate from commercial database engines, you can use the AWS Database Migration Service for a secure migration with minimal downtime.

Amazon Aurora Parallel Query 

Amazon Aurora Parallel Query is a feature of the Amazon Aurora database that provides faster analytical queries over your current data, without having to copy the data into a separate system. It can speed up queries by up to two orders of magnitude, while maintaining high throughput for your core transactional workload.

While some databases can parallelize query processing across CPUs in one or a handful of servers, Parallel Query takes advantage of Aurora’s unique architecture to push down and parallelize query processing across thousands of CPUs in the Aurora storage layer. By offloading analytical query processing to the Aurora storage layer, Parallel Query reduces network, CPU, and buffer pool contention with the transactional workload.

It refers to the ability to push down and distribute the computational load of a single query across thousands of CPUs in Aurora’s storage layer. Without Parallel Query, a query issued against an Amazon Aurora database would be executed wholly within one instance of the database cluster; this would be similar to how most databases operate. Parallel Query is a good fit for analytical workloads requiring fresh data and good query performance, even on large tables. Workloads of this type are often operational in nature. Some of the benefits Faster performance: Parallel Query can speed up analytical queries by up to 2 orders of magnitude.

Use Cases:

Enterprise Applications

Amazon Aurora is a great option for any enterprise application that can use a relational database. Compared to commercial databases, Amazon Aurora can help cut down your database costs by 90% or more while improving the reliability and availability of the database. Amazon Aurora being a fully managed service helps you save time by automating time-consuming tasks such as provisioning, patching, backup, recovery, failure detection, and repair.

Software as a Service (SaaS) Applications

SaaS applications often use architectures that are multi-tenant, which requires a great deal of flexibility in an instance, and storage scaling along with high performance and reliability. Amazon Aurora provides all of these features in a managed database offering, helping SaaS companies focus on building high-quality applications without worrying about the underlying database that powers the application.

Web and Mobile Gaming

Web and mobile games that are built to operate at a very large scale need a database with high throughput, massive storage scalability, and high availability. Amazon Aurora fulfills the needs of such highly demanding applications with enough room for future growth. Since Amazon Aurora does not have any licensing constraints, it perfectly fits the variable usage pattern of these applications.

Performance and Feature Comparison:

Amazon Aurora vs. RDS 

The main benefits of Amazon RDS are its pre-configured parameters, automatic software patching capabilities, and robust tools for monitoring and metrics.

As a custom engine for RDS, Amazon Aurora has additional features to make it faster and more modern. Aurora has high throughput, storage auto-scaling, and a self-healing, fault-tolerant storage system. It also provides point-in-time recovery and continuous backup, with replication across three availability zones keeping your data secure. Aurora vs. RDS performance depends on which engine you use with RDS, as some of them are not optimized for speed but for availability, or to fit in with existing code.

Aurora vs. MySQL and SQL Server

For Aurora vs. MySQL, Aurora is intended for performance with cloud servers, while MySQL is designed to run on physical machines, and may not be optimized for virtual machine performance. As a result, Amazon Aurora vs. MySQL performance will be affected by the nature of the machines the system is running on—physical or virtual. Amazon asserts Aurora is five times faster than standard MySQL databases and three times faster than PostgreSQL databases when used in the cloud. A comparison of Amazon Aurora vs. SQL Server yields similar findings, since SQL Server, like MySQL, is designed to be used on-premises.