Building the Right Architecture for the Job

Gogula Aryalingam takes us through an example where the newest and most expensive tools aren’t the best for the job at hand:

When Azure SQL Data Warehouse was chosen to implement a multi-dimensional data warehouse, it may have seemed like the ideal choice. Why? because it was plain to see: keywords: “SQL”, “Warehouse”. However, no, SQL Data Warehouse is ideal only when you have data loads that are quite high, not when it is only several 100GBs. Armed with a few more reasons as to why not (A good reference for choosing Azure SQL Data Warehouse), I had confronted them. But the rebuke then was that they did get good enough performance, and that cost wasn’t a problem. Until of course a few months later when complex queries started hitting the system, and despite being able to afford that cost, the value of paying that amount did not seem worth it.

Having a good architectural understanding of the Azure or AWS platform—even if you aren’t deeply familiar with all of the tools—can help avoid these types of problems.

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