A Study of MongoDB Data Models and A Novel Hybrid Data Modeling Approach

NoSQL databases have become increasingly popular. With the introduction of Web 2.0, mobile apps such as Facebook, Twitter, and Whatsapp produce massive amounts of unstructured data on a regular basis. Today's difficult task is to effectively manage such data. Many businesses are turning to NoSQL databases to manage massive amounts of data. These NoSQL databases fall in one of the categories viz. key/value, columnar, document oriented, graph-based databases. MongoDB is most popular NoSQL document-oriented database. MongoDB is capable of handling tasks such as search recommendations, cloud management, metadata storage, merchandise categorization, and so on. One of eBay's functionality is search recommendations, which are available on the website. MongoDB responds easily with all of the search suggestions. Many websites and organizations rate MongoDB among the top five NoSQL databases in the world. The main task in a database application is schema design. The behavior of MongoDB in relation to evolving modelling styles is investigated in this paper. The study demonstrates some primary characteristics discovered during MongoDB data modelling. To boost the database, a novel approach of Hybrid data modelling is suggested.