Thinking about different sizes
When you look at your engineered requirements and go through all the Azure data services that can form a modern data warehouse, you still might find it complex to decide which services to pick. And with the generic reference architecture in mind, there is no silver bullet to provision so that everything is fine. But let's examine some considerations about sizes, performance, and cost. One of the beauties of the cloud in general, and the ADS framework on Azure in particular, is that you can always switch gears once you recognize your system is too small, you need far more punch for your calculations, or to ensure speed for your users. Don't get me wrong – some services can be cumbersome to replace. However, it is still far easier to replace something than to rebuild everything from scratch.
Let's check out the three different sizes of modern data warehouse by using S, M, and L as rough indicators of our requirements.
