In the last chapter, we implemented a sample application exposing a read-only service that provided catalog data. For the sake of simplicity, we introduced a performance bottleneck in this implementation by using file storage. This storage is not suitable for web applications. It relies on 33 physical files, preventing our application from servicing heavy loads, as file storage lacks multitenant support due to disc I/O operations. In other words, we definitely need to look for a better storage solution, which scales easily, when needed, following the demands of our REST-enabled application. NoSQL databases are now heavily used in web and in cloud environments, ensuring zero downtime and high availability. They have the following advantages over traditional transactional SQL databases:

• They support schema versions; that is, they can work with object representations rather than filling the object state based on definitions of one or several tables.
• They are extensible, because they store an actual object. Data evolution is supported implicitly, so all you need to do is call the operation that stores the modified object.
• They are designed to be highly distributed and scalable.

Nearly all modern NoSQL solutions out there support clustering and can scale further, along with the load of your application. Additionally, most of them have REST-enabled interfaces over HTTP, which eases their usage over a load balancer in high-availability scenarios. Classical database drivers are usually not available for traditional client-side languages, such as JavaScript, because they require native libraries or drivers. However, the idea of NoSQL originated from using document data stores. Thus, most of them support the JSON format, which is native to JavaScript. Last but not least, most NoSQL solutions are open source and are available for free, with all the benefits that open source projects offer: community, examples, and freedom!

In this chapter, we will take a look at the MongoDB NoSQL database and the Mongoose module that interacts with it. We will see how to design and implement automated tests for the database models. Finally, at the end of the chapter, we will remove the file storage bottleneck and will move our application to an almost ready for production state.