Industry Use Case of MongoDB

What is MongoDB ?

MongoDB is an open-source document-oriented database. It is used to store a larger amount of data and also allows you to work with that data. MongoDB is not based on the table-like relational database structure but provides an altogether different mechanism for storage and retrieval of data, that’s why known as NoSQL database. Here, the term ‘NoSQL’ means ‘non-relational’. The format of storage is called BSON ( similar to JSON format).

How MongoDB works?

some important parts of MongoDB ;

  • Drivers: Drivers are present on your server that are used to communicate with MongoDB. The drivers support by the MongoDB are C, C++, C#, and .Net, Go, Java, Node.js, Perl, PHP, Python, Motor, Ruby, Scala, Swift, Mongoid.
  • MongoDB Shell: MongoDB Shell or mongo shell is an interactive JavaScript interface for MongoDB. It is used for queries, data updates, and it also performs administrative operations.
  • Storage Engine: It is an important part of MongoDB which is generally used to manage how data is stored in the memory and on the disk. MongoDB can have multiple search engines. You are allowed to use your own search engine and if you don’t want to use your own search engine you can use the default search engine, known as WiredTiger Storage Engine which is an excellent storage engine, it efficiently works with your data like reading, writing, etc.

Working of MongoDB –

The following image shows how the MongoDB works:

MongoDB work in two layers –

  • Application Layer and
  • Data layer

Application Layer is also known as the Final Abstraction Layer, it has two-parts, first is a Frontend (User Interface) and the second is Backend (server). The frontend is the place where the user uses MongoDB with the help of a Web or Mobile. This web and mobile include web pages, mobile applications, android default applications, IOS applications, etc. The backend contains a server which is used to perform server-side logic and also contain drivers or mongo shell to interact with MongoDB server with the help of queries.

These queries are sent to the MongoDB server present in the Data Layer. Now, the MongoDB server receives the queries and passes the received queries to the storage engine. MongoDB server itself does not directly read or write the data to the files or disk or memory. After passing the received queries to the storage engine, the storage engine is responsible to read or write the data in the files or memory basically it manages the data.

Some of the industry use-cases of MongoDB:

MongoDB Case Study: Intuit

Intuit empowers small businesses, accountants, and individuals with tax preparation and financial software. In addition, the company enables small businesses to build websites without any technical expertise through its Intuit Websites arm. In order to recommend conversion and lead generation improvements to their customers, Intuit needed a way to collect and analyze data from these sites. Initially, the company tried off the shelf products like Google Analytics and Omniture, but they realized that with more than 500,000 hosted websites and 10 years worth of user data, they required a simple, high-performance solution. With querying and map reduce functionality, MongoDB was the best platform to suit Intuit’s needs.

One of the primary challenges that Intuit faced in trying to make recommendations to their customers was that their existing analytics data was scattered over multiple sources. This posed technical and logistical problems, and prevented analyzing this data in a timely fashion. Due to the distributed nature of their systems and sheer abundance of data, Intuit encountered difficulties when attempting to build their analytics service using a relational database like MySQL or Oracle.

MongoDB provided a solution that was not only easy to deploy, but comparatively more efficient than the other relational and non-relational choices evaluated. Intuit spent a mere week developing a prototype analytics solution based on MongoDB. In that short time, the team was able to become proficient in MongoDB development. As Nirmala Ranganathan of Intuit put it, ……Within one week we had made big progress. Very big progress. It was so amazing that we decided let’s go with this. In addition, Intuit found MongoDB to be 2.5 times faster for writes than MySQL and overall, superior to both relational and non-relational options.

Comprehensive and effective, the MongoDB solution has converted Intuit engineers into enthusiastic members of the MongoDB community. Indeed, not long after deploying their app, the team at Intuit was contributing back to the local MongoDB community with a presentation of their own at the next MongoDB event in the Bay Area.

I Hope You Like It…

Thank You For Reading…

If you like it please clap it.😁🤗

Connect with me on LinkedIn | GitHub

Lifelong learning technologies