How Industries are using MongoDB ?

Ananya Sharma
5 min readSep 27, 2021

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MongoDB is an open-source, schemaless, document-oriented platform also classified as NoSQL database program. In simple terms what happens in MongoDB is, unlike the traditionally used method of creating tables where you create a separate field (column) for every new information you want to add in any record (row) in relational database like SQL, you can create records with there own metadata. The way the data is stored in MongoDB is not in rows and columns but in key-value pairs using JSON.

So, along with providing the features that SQL do, it provides features more than that classifying it to be called as a NoSQL (Not Only SQL).

The tables stored in MongoDB database are called Collections and the records entered in MongoDB are thus known as document hence making it Document Oriented Database.

Schema less:- As stated earlier, the way data stored in MongoDB is not the same as the relational databases. MongoDB works on schema less database where the raw data taken in is in the JSON format as shown below.

{ 
name : "Ananya", age : 24, gender : "female" , interests : "tennis" }{name : "Aman", age : 30, job : "Salesman" }

With JSON-style documents which can have varying sets of fields with different data types for each field. In the schema less database, the system namespace contains an explicit list of collections and indexes where collections may be implicitly or explicitly created and indexes must be explicitly declared.

Advantages of Schema Less

In relational databases like SQL, data needs to be heavily formatted and shaped to fit into the table structure. This means sacrificing any undefined details during the save, or storing valuable information outside the database entirely.

A schema less database, like MongoDB, does not have these up-front constraints, mapping to a more ‘natural’ database. Schema less database provides the following advantages:

  • Greater flexibility over data types: By operating without a schema, schema less databases can store, retrieve, and query any data type which is perfect for big data analytics and similar operations that are powered by unstructured data.
  • No pre-defined database schemas: The lack of schema means that your NoSQL database can accept any data type including those that you do not yet use.
  • No data truncation: A schema less database makes almost no changes to your data; each item is saved in its own document with a partial schema, leaving the raw information untouched. This means that every detail is always available and nothing is stripped to match the current schema.
  • Suitable for real-time analytics functions: With the ability to process unstructured data, applications built on NoSQL databases are better able to process real-time data, such as readings and measurements from IoT sensors.
  • Enhanced scalability and flexibility: With NoSQL, you can use whichever data model is best suited to the job. Graph databases allow you to view relationships between data points, or you can use traditional wide table views with an exceptionally large number of columns. You can query, report, and model information however you choose. And as your requirements grow, you can keep adding nodes to increase capacity and power.

All these features leads to the following key points why companies and developers are using MongoDB:

  • The document data model is a powerful way to store and retrieve data that allows developers to move fast.
  • MongoDB’s horizontal, scale-out architecture can support huge volumes of both data and traffic.
  • MongoDB Represent data with natural clusters and variability over time or in its structure
  • MongoDB support rapid iterative development.
  • MongoDB enable collaboration of a large number of teams
  • MongoDB scale to high levels of read and write traffic.
  • MongoDB Scale your data repository to a massive size.
  • MongoDB evolve the type of deployment as the business changes.
  • MongoDB store, manage, and search data with text, geospatial, or time series dimensions.
  • MongoDB has a great user experience for developers who can install MongoDB and start writing code immediately.

Still there are times when it is better not to use a MongoDB like :

  • Data is structured data.
  • Data is extremely relational (e.g., Social Media), i.e., Graph like data.
  • For Data Warehousing (OLAP database).
  • Multi-Master write is needed for write-heavy loads.
  • High availability is preferred over Consistency.

MongoDB is being used in the following fields:-

Financial Services:-

With the help of data as a service MongoDB provides agility to the work. It provides single view feature by aggregation of multiple data into single repository which provide a firmwide view of asset and counterparty exposure or a single view of your customer for fraud detection and Know Your Customer (KYC) requirements. It helps in real-time data analysis with faster response-time.

Telecommunication:-

Telecommunication thrives on AI and IOT and MongoDB is very friendly to work with them and along with 5G single view and faster response again adding up to its advantage.

Healthcare:-

MongoDB apart from its features of fast response and single view also has the Graphic User interface which helps in building FHIR applications which helps in the data interoperability.

Gaming:-

Data has always been an essential part of video games. And now that Modern games are multiplayer and online, reach massive scale, and must evolve quickly to stay relevant. From player profiles to telemetry, matchmaking to leaderboards, data is crucial to making games work — and making them better.

Retail:-

Preserving costumer information is something very important nowadays also that artificial intelligence has come to play in almost every field. MongoDB with its features tries to provide an omnichannel consumer experience that integrates all online, social, and in-person interactions.

Payments:-

Consumers today expect quick, seamless payment transactions without any mistake. Banks, payment service providers (PSPs), and other industry participants have to meet these expectations while adhering to constantly shifting regulations. MongoDB provides evolving customer expectations, comply with regulations with an agile approach to data.

Thanks for reading :)

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