Let's start by exploring the answers to the question, what exactly is a NoSQL database? NoSQL is a common term for database technologies that deviate from the traditional Relational Database Management System (RDBMS) concepts. The common reason for these database solutions to deviate from RDBMS database standards is to achieve and set a better standard of availability and partitioning capabilities than traditional RDBMS solutions.

To introduce you to this concept, we should have a look at the Brewer's theorem, which is otherwise known as the CAP theorem:

"It is impossible for a distributed computer system to simultaneously provide all three of the following guarantees: Consistency, Availability, and Partition tolerance."

Traditional RDBMS solutions are good at consistency and compromise a little once it comes to providing better availability (data reads) and partitioning capabilities. Most of the NoSQL solutions have been evolved in this direction to achieve better heights in data availability and partitioning.

As this is a common term for any database technology that deviates from the concepts followed by RDBMS solutions such as MySQL, PostgreSQL, and so on, there are various subsets for NoSQL databases. Most popular subsets of NoSQL are document stores, key-value stores, and graph-based database solutions. MongoDB, which is the one we are going to try out, falls in the document store category. There are many more NoSQL solutions available in the market apart from MongoDB, such as Cassandra, Redis, Neo4j, Hbase, and so on.