Amazon has made its high performance MySQL-compatible database available to all customers.

Amazon Aurora is a MySQL-compatible database engine that has been showing performance of up to five times better than MySQL during a preview where more than a thousand Amazon Web Services (AWS) customers tried the database. The companies taking part in the preview used Aurora for everything from massive Internet of Things (IoT) applications to mission-critical e-commerce sites, according to Amazon.

Writing about the new availability on the Amazon AWS blog, Jeff Barr said that customers:

“verified that each Amazon Aurora instance is able to deliver on our performance target of up to 100,000 writes and 500,000 reads per second, along with a price to performance ratio that is 5 times better than previously available.”

Aurora is designed to be highly durable and available, which it achieves by automatically replicating data across multiple Availability Zones and continuously backing up data to Amazon Simple Storage Service (Amazon S3). It is designed to offer greater than 99.99 percent availability and automatically detect and recover from most database failures in less than 60 seconds, without crash recovery or the need to rebuild database caches.

At the moment Amazon Aurora is available as a database engine for Amazon Relational Database Service (Amazon RDS) in the US East (N. Virginia), US West (Oregon), and EU (Ireland) Regions. Support for additional Regions will be added in the next few months. Amazon RDS for MySQL customers can convert their existing MySQL databases to Amazon Aurora with one click in the AWS Management Console.

When the preview was first announced, see Amazon Launches Supercharged MySQL Alternative, Jeff Barr said that all the databases Amazon has until now offered on its RDS relational database service (MySQL, Oracle, SQL Server, and PostgreSQL), were

“designed to function in a constrained and somewhat simplistic hardware environment -- a constrained network, a handful of processors, a spinning disk or two, and limited opportunities for parallel processing or a large number of concurrent I/O operations”.

To overcome this Aurora was created to be designed for the cloud, with an integrated design encompassing the storage, network, compute, system software, and database software.

Aurora is built on an SSD-based virtualized storage layer designed for database workloads, and as you need more storage, Aurora adds it in 10 GB increments on as as-needed basis, all the way up to 64 TB. Barr said at launch that the baseline storage performance is rapid, reliable and predictable, scaling linearly as you store more data, and letting you burst to higher rates on occasion.

Aurora is fully compatible with MySQL in areas such as table structures and SQL calls, but is easier to administer, as it avoids the need to manage data replication because six copies of the data are automatically replicated across three Availability Zones. Hardware failure is also less of a problem as the data is backed up to the Amazon Simple Storage Service (S3) rather than needing to be backed up using snapshots. Aurora detects any database failures and transparently recovers with instance restarts typically requiring less than a minute. If the failure is permanent, will automatically failover to a replica without losing any data.

As we reported at its launch, Aurora provides similar performance and availability as high-end commercial database offerings, but at one tenth of the cost with no minimum commitment or up-front fees. Pricing is based on what you actually use, starting at 29 cents per hour for 15.25GB of memory and two virtual CPUs. You then pay separately for storage at 10 cents per gigabyte per month, and I/O at 20 cents per million requests. 

A webinar giving more details and showing Aurora in action is scheduled for August 19. 

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