MongoDB – An Exceptional NoSQL Database

With huge gamut of unstructured data gripping the systems across the world and with the consequent incompetencies of the overflowing RDBMS’, surged the need of an efficient database that excels in storing infinite data with utmost ease and with well-sustained high-level performance. Thus, came in MongoDB – a NoSQL database, literally translating into a “not only SQL” humongous database that steps beyond SQL limitations and outshines every other traditional relational database in terms of high scalability, high performance, high availability, and high capacity in providing effective back-end storage for high-traffic websites.

MongoDB – A Product of Principled Engineering?

It is strange yet factual enough to state that MongoDB is far from being adjudged as a product of principled engineering. MongoDB has three different data access layers thereby sometimes earning the title “The Frankenstein Monster of NoSQL Databases” (De Goes). The author of the article “MongoDB: The Frankenstein Monster of NoSQL Databases” draws an analogy when he compares MongoDB with Mary Shelley’s monster Frankenstein. He claims that much like Frankenstein, who was created by sewing together varied parts from different bodies, MongoDB is also created with varying layers that are difficult to fit in together, but have got aligned in such a way that it works extraordinarily well.  Therefore, despite its regularly imbricating layers that overlap in functionality, MongoDB has emerged as one of the successful databases that web pioneers had dreamt of – a powerful database with exceptional horizontal scalability and flexible data model.

Why is MongoDB Leading?

JSON or BSON Data Storage: Unlike other relational databases where data is stored in the columns and rows, in MongoDB the data is stored as documents, which may include subdocuments. In this light, Will Shulman, the CEO of MongoLab points out:

The disproportionate success of MongoDB is largely based on its innovation as a data structure store that lets us more easily and expressively model the “things” at the heart of our applications….

Power Performance: With increased internet access and other systems available to the world, there has risen a heavy, and largely unmanageable, traffic flow to the websites. Countering this flow, MongoDB has become one of the primary providers of back-end support system. MongoDB has proved itself as the leading database that excels in managing and supporting storage for websites with heavy traffic flows.

Horizontal Scaling – A Boon

Unlike Vertical Scaling Approach, where one usually adds more CPU or RAM, to the existing server in order to increase its capacity, in Horizontal Scaling Approach or Sharding, as it is called, scaling of the database can be done through different servers instead of using one server, thereby decreasing to minimum the maintenance efforts and cost expenses. MongoDB, as a NoSQL database has horizontal scaling at its disposal, therefore, making it way better than other databases.

With high scalability, high availability, auto-sharding, and many other appreciable features to its credit, MongoDB has certainly become the most favoured NoSQL database, with Google Search and Linkedin Profiles proving it true. Millions of searches on Google and the equivalent number of Linkedin Profiles with MongoDB as a ringing keyword have come up to yell to the world that MongoDB is a sure-shot SUCCESS!

Successful it is! And with its success comes up a need to learn MongoDB. ETLhive delivers brilliant training lectures on MongoDB, and on its functionality in me MEAN Stack. ETLhive offers the best training course in MEAN stack in which it covers all the four connectors that make up MEAN Stack namely MongoDB, Express, AngularJS, and node.js. The course throws light on all other significant concepts such as the Collaboration of MongoDB and Node.js; Mongoose, Schema, Validation; the collaboration between Express and Node.js; Express Middleware, and many more. Join ETLhive to get the best of training that is possible in MongoDB and MEAN Stack.