MySQL face-off: Amazon Aurora outscales Google Cloud SQL

Google Cloud SQL performance may beat Amazon Aurora at low thread counts, but Aurora owns the high end

At a Glance

Many web applications have been built on an open source stack that included MySQL. Despite its limitations, MySQL managed to become the world’s most widely used open source RDBMS. What limitations, you ask? Out of the box, MySQL does not scale all that well and, in particular, cannot handle a lot of simultaneous clients compared to commercial databases.

Amazon Aurora and Google Cloud SQL were both developed to offer customers high-performance, high-scalability MySQL databases as a service. Each works best as part of an application stack residing not only in the same cloud provider, but also in the same availability zone, to minimize the latency between services and maximize the network throughput within the stack.

I benchmarked and reviewed Amazon Aurora about a year ago. More recently I previewed Google Cloud SQL. In this article, I’ll tell you what happened when I benchmarked Google Cloud SQL against Amazon Aurora using a transactional load with a varying number of client threads.

Benchmarking SQL in the cloud 

Benchmarks are really hard to perform correctly. 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.”

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