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Caching a MongoDB Database with Redis

Today, performance is one of the most important metrics you need to evaluate when developing a web service. Keeping customers engaged is critical to any company, especially startups, and for this reason it is extremely important to improve the performances and reduce page load times.

When running a web server that interacts with a database, its operations may become a bottleneck. MongoDB is no exception here, and as your MongoDB database scales up, things can really slow down. This issue can even get worse if the database server is detached from the web server. In such systems, the communication with the database can cause a big overhead.

Luckily, you can use a method called caching to speed things up. In this tutorial we’ll introduce this method and see how you can use it to enhance the performance of your Node.js web service.


Caching is a strategy aimed at tackling the main storage problem, which means: the bigger the storage is, the slower will be, and vice versa. In a computer, you have the hard drive which is big but also relatively slow. You then have the RAM which is faster but smaller in its storage capabilities, and lastly the CPU registers which are very fast but tiny.

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