Amazon cloud database graduates into general availability
Hosted Oracle, MySQL, SQL Server DB gets SLA to boost biz adoption
Amazon's cloudy database service has donned its cap and graduated into general availability, after three and a half years of dealing with data workloads.
The graduation of the Amazon Web Services Relational Database Service (AWS RDS) was announced by Amazon on Thursday, and along with the standard round of back-patting and reminders of early successes, AWS RDS has been given an SLA to boost biz adoption.
"Amazon RDS is now being used in mission-critical deployments by tens of thousands of businesses of all sizes," beamed Amazon evangelist Jeff Barr in a blog post on Thursday. "We now process trillions of I/O requests each month for these customers. We're seeing strong adoption in enterprises such as Samsung and Unilever, web-scale applications like Flipboard and Airbnb, and large-scale organizations like NASA JPL and Obama for America."
AWS RDS has been given an uptime SLA of 99.95 per cent, so if it goes down for more than 22 minutes in any month, users can ask Amazon for a refund for the downtime. The SLA is an explicit attempt by Amazon to deal with any potential misgivings companies may have about keeping the engines of their businesses in the cloud.
"The new Amazon RDS SLA is designed to give you additional confidence to run the most demanding and mission critical workloads dependably in the AWS cloud," Barr wrote.
The hosted database supports Oracle, MySQL, and SQL Server. With the recent launches of Windows Azure and Google Compute Engine, Amazon is facing more competition for hosted database services, and we think this could be a motivation behind offering an SLA against the tech.
Since AWS RDS's launch in October 2009, the service has been given a mammoth set of improvements by Amazon, with added features like reserved instances and easy spin-up and spin-down of read replicas.
But unless businesses are generating data in the AWS cloud, getting information in and out of AWS RDS can be tricky, and if the data is coming from on-premise repositories and changes a lot, then getting it into the cloud in a timely manner can be expensive. ®
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