What MongoDB is?
MongoDB is an open-source document database and leading NoSQL database. MongoDB is written in C++.
MongoDB is a cross-platform, document-oriented database that provides, high performance, high availability, and easy scalability. MongoDB works on the concept of collection and document.
Pros of MongoDB why it is used over other Databases?
- MongoDB has a lower latency per query & spends less CPU time per query because it is doing a lot less work (e.g. no joins, transactions). As a result, it can handle a higher load in terms of queries per second and is thus often used if you have a massive load of users.
- MongoDB is easier to share (use in a cluster) because it doesn’t have to worry about transactions and consistency.
- MongoDB has a faster write speed because it does not have to worry about transactions or rollbacks (and thus does not have to worry about locking).
- MongoDB does not have a schema in case you have a special use case that can take advantage of that.
Features of MongoDB
- It is schema less so it provides the flexibility to add the fields on the fly.
- The data model available within MongoDB allows you to represent hierarchical relationships, to store arrays, and other more complex structures more easily.
- MongoDB arrange the data structured as in form of class and object so it provides the better understanding to the developer who have knowledge of programming language and using this database.
Use Case of MongoDB in Aadhar Card:
As Aadhaar continues to enroll thousands of Indians each day and add terabytes of data to its Central Identity Data Repository, MongoDB and other data management and analytics software providers continue to produce insights that will aid Aadhaar and the lives of millions of India’s BoP citizens.
In November 2013, it was announced that MongoDB’s CEO, Max Schireson, was in New Delhi to complete talks with the Unique Identification Authority of India (UIDAI) in order for MongoDB to be one of the approved partners for the Aadhaar program MongoDB Inc.
Aadhaar chose to partner with MongoDB (in addition to other vendors such as Hadoop, MySQL, HBase, and Solr) for several reasons. First, 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. Second, 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. Third, 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. Aadhaar has therefore been less dependent on MongoDB and has decided to share more of the data processing volume with its other management vendors.
Use cases of MongoDB in Adobe
MongoDB today announced that Adobe has added support for MongoDB, the database for modern applications, to facilitate the storage of data with the release of version 6.0 of Adobe Experience Manager, the market leader in Web experience management. Experience Manager enables marketers to create, manage and optimize customer-facing digital experiences across all channels, including web, mobile apps, social, video and in-store. Adobe built a version of the persistence layer for Experience Manager 6.0 on MongoDB, which stores petabytes of data that customers need for their large-scale content repositories, for management and delivery of mission-critical digital experiences.
MongoDB tightly integrates with Experience Manager, supporting a modern, world-class digital experience management platform. By introducing a new content repository architecture based on the JCR 2.0 standard, Experience Manager provides customers flexibility for implementing large and distributed repositories while maintaining industry standard compliance for content-centric applications. Experience Manager customers who take advantage of MongoDB can deploy a highly scalable content repository to support their business needs, as well as migrate content from legacy systems.
Use cases of Shutterfly
Shutterfly is a popular internet-based photo sharing and personal publishing company that manages a store of more than 6 billion images with a transaction rate of up to 10,000 operations per second. Shutterfly is one of the companies that transitioned from Oracle to MongoDB.
During the evaluation at the time of transition to MongoDB, it became apparent that a non-relational database would suit the Shutterfly’s data needs better and thereby possibly improving programmer’s productivity as well as performance and scalability.
Shutterfly considered a wide variety of alternate database systems, including Cassandra, CouchDB and BerkeleyDB, before settling on MongoDB. Shutterfly has installed MongoDB for metadata associated with uploaded photos, while for those parts of the application that require richer transactional model, like billing and account management, the traditional RDBMS is still in place.
Till now, Shutterfly is happy with its decision of transitioning to MongoDB and what Kenny Gorman (Data Architect of Shutterfly) has to say about it is, “I am a firm believer in choosing the correct tool for the job, and MongoDB was a nice fit, but not without compromises.”
Conclusion
MongoDB is a popular NoSQL database solution that suits modern development requirements. In this tutorial, we’ve covered the basics of MongoDB, the Mongo shell and some of the popular drivers available. We’ve also explored the common database operations and CRUD actions within the Mongo shell. Now it’s time for you to head out and try what we’ve covered here and more. If you want to learn more, I recommend creating a REST API with MongoDB and Node to acquaint yourself with the common database operations and methods.
