![]() I have also tried a different configuration that I felt would be more representative of the way people might try to use high-performance databases such as Google Cloud SQL and Amazon Aurora. I have now tried to replicate Google’s results. I also qualified any conclusions I drew about comparative performance by saying “according to Google’s results.” In my first look at Google Cloud SQL, I felt I didn’t have the time and resources to reproduce Google’s transactional Sysbench tests of its own Cloud SQL database, Amazon RDS for MySQL, and Amazon RDS for Aurora, so I printed Google’s results with the proviso that they had not yet been replicated by InfoWorld. There were several other configuration subtleties that I worried about, but actually got right, principally an enhanced networking driver and modifications to the Linux network routing settings. ![]() As it turned out, Aurora write rates tend to start high, then level off, and I was running a shorter test than Amazon had. After working with one of the Amazon engineers to diagnose the differences between my configuration and theirs, I changed the availability zone of the clients to match the availability zone of the database and actually recorded higher write numbers than Amazon did. I initially recorded numbers half of what Amazon reported for its read-only and write-only Sysbench tests. They are easy to do wrong, leading to the expression “lies, damned lies, and benchmarks.” And they can be done in ways that are meaningless but sound impressive, leading to the portmanteau “benchmarketing.”įor my review of Amazon Aurora, I more or less reproduced Amazon’s own benchmarks, with some difficulty. ![]() ![]() Benchmarks are really hard to perform correctly. ![]()
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