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Did you try amazon-rds? How is it, performance-wise?
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It's easy to get started: just log into the Amazon RDS Management Console, and enable Performance Insights when creating or modifying an instance of a supported RDS engine. Then go to the Performance Insights dashboard to start monitoring performance.
An Amazon RDS performance best practice is to allocate enough RAM so that your working set resides almost completely in memory. The working set is the data and indexes that are frequently in use on your instance. The more you use the DB instance, the more the working set will grow.
Customers are responsible for managing their data (including encryption options), classifying their assets, and using IAM tools to apply the appropriate permissions. This customer/AWS shared responsibility model also extends to IT controls.
I think this is a hard question to answer as it is highly specific to the problem you are trying to solve, but I will try to give you a picture of what we have seen.
We have been benchmarking RDS using CloudWatch metric gathering tools (provided here: http://aws.amazon.com/articles/2934) and have found it does perform nearly as well as our production servers for our data set. We tested both with a single RDS instance and with a Multi-AZ setup (what we plan to use in production) with no back-up retention.
The load we have been able to throw at it so far we are able to get up into the 1000-1100 Write IOPS range (their metric) even on a small database instance (db.m1.small). At least for our load, increasing the instance class did not affect our throughput IOPS or Bytes. We saw about a 10% reduction in performance when
Amazon freely admitted up front that the solution to really scale out is to subdivide your problem such that you can scale/store it across multiple database servers. We in fact have this in our application (very similar to sharding) and therefore will be able to take advantage and very easily move past this IOPS measurement.
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