Notes about Cutting-Edge Technologies and Everything

In terms of performance tuning in Snowflake, there are very few options available. However, it is worth understanding how the Snowflake architecture includes various levels of caching to help speed your queries. This article provides an overview of the techniques used, and some best practice tips on how to maximise system performance using caching. Snowflake Database Architecture Before starting it’s worth considering the underlying Snowflake architecture, and explaining when Snowflake caches data. The diagram below illustrates the overall architecture which consists of three layers:- Service Layer:   Which accepts SQL requests from users, coordinates queries, managing transactions and results.  Logically, this can be assumed to hold the  result cache  – a cached copy of the results of every query executed. Compute Layer:   Which actually does the heavy lifting.  ...

Great article by Sarah Mei explaining when and how using a document model can lead to complex application code and bad performance. " When you’re picking a data store, the most important thing to understand is where in your data — and where in its connections — the business value lies. If you don’t know yet, which is perfectly reasonable, then choose something that won’t paint you into a corner. Pushing arbitrary JSON into your database sounds flexible, but true flexibility is easily adding the features your business needs. " Why You Should Never Use MongoDB: http://www.sarahmei.com/blog/2013/11/11/why-you-should-never-use-mongodb/