One of the biggest challenges for databases is caching data, and this is one area where NoSQL is superior to SQL in a lot of respects. The cache solutions available for NoSQL are particularly good. With NoSQL you have some high-speed caching options available, which means that you can handle a lot of queries very quickly.

NoSQL offers high-speed cache solutions that keep a lot of information in memory, without you needing to have an additional cache layer at the application level. This makes it easier to create high-performance applications that can handle large amounts of data and a high volume of simultaneous users without issues.

Solutions for Faster NoSQL Cashing

There are a couple of additional caching options that are available, including Memcached and Redis. On paper, Memcached is usually the most efficient option, but it is not uncommon for Redis to end up being the best choice. Memcached is the more mature technology – it was developed back in 2003, for LiveJournal. It was created in Perl at first, but has since been rewritten from the ground up in C. It is used in a huge number of modern Web apps, and it has reached the stage where it is now considered to be ‘feature complete’, with new versions focusing on optimization and stability updates, rather than expanding the feature set.

Redis is not an immature solution by any means. It was released in 2009, and it makes a number of improvements on Memcached. They have the advantage of being the second to market so they got to see a lot of the mistakes that Memcached made, and they have been able to avoid those mistakes and iterate on the good decisions that Memcached made. Redis is not quite as fast as Memcached for some use-cases, but it is no slouch. It is an in-memory caching application, and it is very easy to set up and use, offering a huge improvement in performance.

Redis Vs Memcached

Memcached is great for working with small amounts of data, especially if the data is relatively static. It has efficient memory management, and it does not use a huge amount of memory for storing metadata. So, for Strings, it’s a great choice. Memcached is also highly scalable, since it is multithreaded, although you may lose a small amount of the cached data when you scale up.

Redis is primarily a single-threaded system. It can scale via clustering without data loss, but it is more work to do this. Redis shines when you need to use data structures, and it also has some nice options for data eviction. Instead of simply ditching the data that was used least recently, Redis gives you more control over what gets kept and what is discarded, which can be useful for larger applications. Redis lts you store a lot more data types and updating the cache value is simple and not particularly resource intensive.

Whatever option you use, you will find that NoSQL with a good caching system offers high performance for large amounts of data.