Yesterday, GigaOm published a benchmark of Azure SQL Database as compared to Amazon’s RDS service. It’s an interesting test case that tries to compare the performance of these platform as a service database offerings. One of the many challenges of this kind of a study is that the product offerings are not exactly analogous. However, GigaOm was able to build a test case where they used similar sized offerings as shown in the image below.
GigaOm used TPC-E which is a blended OLTP workload which involves both read-only and update transactions. In the raw performance numbers, SQL DB was a little bit better in terms of overall throughput, but where Azure really shines in comparison to AWS is pricing.
In terms of raw pricing, there is a significant difference between Azure SQL DB and AWS pricing for these two instances. Azure is $25,000/month less, however it’s not quite an apples to apples comparison, as Azure SQL DB is single database service as opposed to RDS which acts more like Managed Instance, or on-premises SQL Server. If you use use the elastic pool functionality in Azure SQL DB which is the same cost as single database SQL DB, you get a better comparison.
Where the real benefits come in, are that Microsoft allows you to bring on-premises licenses to Azure SQL Database, and the fact the Microsoft offers a much lower cost for 3 year reservations. (Which you can know pay for on a month to month basis). This is a big advantage that Microsoft has over Amazon is that they control the licensing for SQL Server. You can argue that this isn’t fair, but it’s Microsoft’s ball game, so they get to make the rules.
There will always be an inherent feature advantage to being on Azure SQL DB over AWS RDS, as Microsoft owns the code and can roll it out faster. While AWS is a big customer, and will be quick to roll out new updates and versions, they are still subject to Microsoft’s external release cycle whereas Azure is not. In my opinion, if you are building a new PaaS solution based on SQL Server, your best approach is to run on Azure SQL DB.
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