Case study and Industrial Use Cases of MongoDB

MongoDB is one of the newest competitors in the field of Data Storage. Still, it has become very popular with its document-oriented NoSQL Features, Map Reduce calculation capability, and distributed key-value store. It has got the title of “Database Management System of the Year” by DB-Engine.

MongoDB Features

Mobility and Scaling

MongoDB is very scalable and flexible, which gives fantastic database solutions to deal with different kinds of environments. The schemas of MongoDB will evolve over time, and in this way, mobile application developers can focus their time on developing better customer experience.

 Real-Time Data Integration

There is a lot of value to data if it is consolidated and aggregated into one single view, and MongoDB plays a vital role in doing that. Due to the query capabilities and flexibility of MongoDB, now it is easier to aggregate data and create those tools which will make an organization more efficient.

Product Catalog

There are many attributes to products which are easily stored as an object using MongoDB and can be used to understand the customer better in the digital experience. MongoDB has dynamic schema capability, which helps in bringing relevancy between attributes and product documents.

Consistency over Availability

If one prefers consistency over availability, then he can get a specific version of Consistency in MongoDB applications.

Data on Single Server

One of the best features of MongoDB is that it was made intentionally sub-optimal to enable sharding on a single server. But you can use PostgreSQl, If the data fits on a single server comfortably.

Ideal for Querying

If the rate of querying is very strong to the database, then Mongo is ideal to be used because it resembles a DWH cube in its basic data structure.

MongoDB uses -

Balanced Features 

One can use MongoDB to get multiple balanced features. For example, that one wants to use some features like Queuing, Map/Reduce, FTS but don’t require it a lot, which is easily possible through MongoDB.

Polyglot Database System

MongoDB has an excellent capability to pick up the best part of all the databases, which makes it even more amazing to use as large-scale systems that are not using only a single database.

Gaming

MongoDB’s flexible document data model allows you to quickly iterate on what constitutes a player in your world. Add and associate new features to player profile objects such as achievements, progression-based unlocks, in-game currency, new classes of gear, and more. Keep your players protected with enterprise-grade security controls at the data layer.

Payments

If you’re designing a new payments product MongoDB's data agility allows new products to get to market quickly, without data fragmentation and unnecessary complexity. If you’re a mature enterprise looking to modernize your payment landscape, leverage MongoDB’s flexibility to use it as a consolidated Operational Data Layer, enabling you to build new services and products rapidly using existing data without a risky rip-and-replace

Data Analytics on Real Time

MongoDB can incorporate any kind of data – any structure, any format, any source – no matter how often it changes. Your analytical engines can be comprehensive and real-time.

Scale Big. MongoDB is built to scale out on commodity hardware, in your data center or in the cloud. And without complex hardware or extra software. This shouldn’t be hard, and with MongoDB, it isn’t.

Real Time. MongoDB can analyze data of any structure directly within the database, giving you results in real time, and without expensive data warehouse loads.

There are many more use cases of MongoDB like Personalization, Single View, Content Management, Mainframe Overloading etc.

Case Study on MongoDB

Aadhar

Adhar is an excellent example of real world use cases of MongoDB. In recent times, there has been some controversy revolving around CIA’s non-profit Venture Capital arm, In-Q-Tel, backing the company, which developed MongoDB.

India’s Unique Identification project, aka Aadhar, is the world’s biggest biometrics database. Aadhar is in the process of capturing demographic and biometric data of over 1.2 billion residents. Aadhar has used MongoDB as one of its databases to store this huge amount of data. MongoDB was among several database products, apart from MySQL, Hadoop and HBase, originally procured for running the database search. Here, MySQL is used for storing demographic data and MongoDB is used to store images.

Why Aadhar use MongoDB

• MongoDB increases database efficiency with its NoSQL approach, which enables Aadhaar to capture, process, search, and analyze large unstructured datasets faster than most other management software would allow.
• MongoDB can efficiently store large volumes of biometric data and images, whereas many other management systems, such as MySQL, are less suited for image storage.
• Aadhaar’s data processing analytics cannot depend solely on a single software supplier. As a result, UIDAI diversified its systems reliance across multiple vendors and leverages each vendor’s strengths.

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