The Amazon Relational Database Service (RDS) was designed to simplify one of the most complex of all common IT activities: managing and scaling a relational database while providing fast, predictable performance and high availability.
RDS in Action
In the 3.5 years since we launched Amazon RDS, a lot has happened. Amazon RDS is now being used in mission-critical deployments by tens of thousands of businesses of all sizes. 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.
As part of recent rebuild of Classcaster, I shifted the MySQL database for the system to Amazon RDS. I found the process of importing an existing database to be straight forward and was up and running in no time. Since it is just an instance of MySQL running in the Amazon cloud, I administer it as I do the other my other MySQL databases running on AWS EC2 instance using SQLyog on Mac and Windows and MySQL Workbench on Linux1» .
As far as performance goes, RDS seems a bit more responsive than the AWS EC2 hosted databases I run. It is important to note that it is possible to knock it over by overloading the connection pool2» . Logging and backups are handled well and access to these from the RDS dashboard is pretty good. Although I haven’t tried it yet, the features exist to scale the database as needed. I may take advantage of some of this if I decide to move our main databases to RDS.
Overall, I’d recommend RDS as a good way to get a database up and running quickly and to provide a stable backed for your systems.