MongoDB: Leading NoSQL Database

What is NoSQL?

NoSQL databases (aka “not only SQL”) are non tabular, and store data differently than relational tables. NoSQL databases come in a variety of types based on their data model. The main types are document, key-value, wide-column, and graph. They provide flexible schemas and scale easily with large amounts of data and high user loads.

NoSQL databases emerged in the late 2000s as the cost of storage dramatically decreased. Gone were the days of needing to create a complex, difficult-to-manage data model simply for the purposes of reducing data duplication. Developers (rather than storage) were becoming the primary cost of software development, so NoSQL databases optimized for developer productivity.

As storage costs rapidly decreased, the amount of data applications needed to store and query increased. This data came in all shapes and sizes — structured, semistructured, and polymorphic — and defining the schema in advance became nearly impossible. NoSQL databases allow developers to store huge amounts of unstructured data, giving them a lot of flexibility.

Cloud computing also rose in popularity, and developers began using public clouds to host their applications and data. They wanted the ability to distribute data across multiple servers and regions to make their applications resilient, to scale-out instead of scale-up, and to intelligent geo-place their data. Some NoSQL databases like MongoDB provided these capabilities.

What is SQL?

Now that we have an understanding of NoSQL databases, let’s contrast them with what have traditionally been the most popular databases: relational databases accessed by SQL (Structured Query Language). You can use SQL when interacting with relational databases where data is stored in tables that have fixed columns and rows.

SQL databases rose in popularity in the early 1970s. At the time, storage was extremely expensive, so software engineers normalized their databases in order to reduce data duplication.

What is MongoDB?

MongoDB is Document-oriented NoSQL database used for storing the data. It is different from other databases due to its no structured or schema less feature. In all the traditional databases there is row and column but, in the MongoDB, we have collections and documents.

Collection contains the multiple documents and functions like the traditional databases have the tables.

Documents contains key-value pair data in the JSON format which are the basic unit of MongoDB.

MongoDB Atlas is global leading cloud database services that can be launched on the top of most famous clouds — AWS, GCP and Azure. It also provides the great security for the databases.

As of 2k20, MongoDB has been downloaded over 30 million times with over 730,000 MongoDB University registrations. More than 10+ language support drivers are already they’re in MongoDB. Best part of this is MongoDB is free to use.

Working with MongoDB:

There’s a bunch of GUIs (Graphical User Interface) to work with MongoDB server such as MongoDB Compass, Studio 3T, and so on.

They provide a graphical interface so you can easily work with your database and perform queries instead of using a shell and typing queries manually.

Features of MongoDB:

1. It is schema less so it provides the flexibility to add the fields on the fly.
2. The data model available within MongoDB allows you to represent hierarchical relationships, to store arrays, and other more complex structures more easily.
3. 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.
4. The document doesn’t need to have schema pre-created you can create it on the fly according to the requirement and attach into it

Benefits:

The following are some of MongoDB benefits and strengths:

• Dynamic schema: As mentioned, this gives you the flexibility to change your data schema without modifying any of your existing data.
• Scalability: MongoDB is horizontally scalable, which helps reduce the workload and scale your business with ease.
• Manageability: The database doesn’t require a database administrator. Since it is fairly user-friendly in this way, it can be used by both developers and administrators.
• Speed: It’s high-performing for simple queries. • Flexibility: You can add n ew columns or fields on MongoDB without affecting existing rows or application performance.

Industries are using MongoDB for following purposes:

1. 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. This will help many companies to deal with varying structures of data that are coming from many different sources in the mobile application development world.

2. 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.

With the help of MongoDB, one can see aggregated data in a single view in real-time, which provides massive value to the companies. A developer can also take quick action on specific events and also monitor with the help of MongoDB 3.6.

3. 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. Nowadays, the quality and volume of data are increasing and are being used to improve the interaction in product catalogs of customers. MongoDB has dynamic schema capability, which helps in bringing relevancy between attributes and product documents. It will provide a better experience for both customers and developers.

Some Real-World use caes of MongoDB:

1. Aadhar :

Aadhar is an excellent example of real-world use cases of MongoDB.

It is India’s Unique Identification project, which has the biggest biometrics database in the world. Aadhar Project is using MongoDB as its database to store a massive amount of demographic and biometric data of more than 1.2 billion Indians. MongoDB is being used for the storage of images in the Aadhar project.

2. 𝐞𝐁𝐚𝐲:

eBay is a multinational company that provides a platform for the customer to customer sales. It is currently running a large number of projects in MongoDB like merchandising categorization, cloud management, metadata storage, search suggestions.

3. Shutterfly:

Shutterfly is one of the most popular online photo sharing, and it is using MongoDB to manage and store more than 6 billion images, which has a transaction rate of up to 10,000 operations per second. Shutterfly earlier used Oracle but later transitioned to MongoDB.

Shutterfly company realized that moving to a non-relational database will help them to increase their scalability, performance, and productivity of the programmer.

Shutterfly did consider many other alternate database systems like BerkeleyDB, CouchDB, or Cassandra. The company has confirmed that they are pleased with their decision of transitioning from Oracle to MongoDB.

Conclusion:

The demand for NoSQL databases like MongoDB has gone up in the recent times. Here are some real-world use cases of MongoDB along with some companies that use MongoDB for their practical applications.

I hope this article will help you understand MongoDB and it’s practical applications… :)