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SQL is an excellent querying language to filter and process data.

One of the often overlooked but critical components of a functioning web application is it’s performance.

For several reasons (detailed below), you should always implement as many caching layers as you can in an application: Now that we’ve covered the general caching strategies and how they should be employed, we’ll do a deeper dive on some of the subtleties you’ll encounter as you implement layered caching.

The first of these is user-specific content and upstream caches.

Even though memcached is a stable and mature caching system, it has subtle nuances that can make it difficult to tame.

Django always gives a polished product within the time.

The key here is generated by hashing the underlying raw My SQL for a given query, while the value is yielded by iterating through the entire Query Set and extracting field values for each object.

On a storage level, Cache Machine extends the built-in Django caching backend to enable infinite cache timeouts.

People complain too much about Django’s code abstraction which makes it slow. For any web stack communication between web application and database is the slowest part.

With bad ORM usage practices we are making it even much slower.