We’re living and working in a data-driven world. So, if you want to make the most of that data, you need organized, easily accessible information. In other words, you need a database. A database is any structured information or data specially organized and stored in a computer for fast retrieval and search.

Okay, that’s great, but there’s a lot of databases out there. So, which is the right one?

MongoDB is a popularly used NoSQL (not only SQL) database. Surely, you would have heard about this several times, if you’re interested in this topic. This tutorial on What is MongoDB will give you a deep understanding of its working and applications.

Now that you know what’s in store for you, continue reading the tutorial;

MongoDB Evolution

Structured Query Language (SQL) existed even before the World Wide Web. However, as websites' functionality grew, developers wanted to generate web pages using content that could change over time without redeploying the code. As a result, Not only SQL or NoSQL was developed. NoSQL has relaxed ACID (atomicity, consistency, isolation, durability) properties and guarantees better performance, scalability, flexibility, and reduced complexity. 

MongoDB was released on August 27th, 2009. Version 1 was basic, while version 2 introduced features like sharding, usable and special indices, geospatial features, memory, and concurrency improvements, among others. Version 3 came with an aggregation framework mainly as a supplement to the aging MapReduce framework.

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What is MongoDB?


MongoDB was created in 2009 as an open-source, highly scalable, robust, and free NoSQL database. It also has a commercial version. You can find MongoDB’s source code on GitHub.

MongoDB has cultivated a reputation as a versatile, flexible database and is currently used today as the backend data store of many high-profile businesses and organizations such as Forbes, Facebook, Google, IBM, Twitter, and many more. 

MongoDB is a non-relational database system. There are two primary database types: SQL (relational) and NoSQL (non-relational). Relational databases store data in columns and rows. Organizations like Microsoft SQL Server Oracle and Sybase use the relational database management system (RDBMS).

On the other hand, NoSQL databases store schema-less, unstructured data in multiple collections and nodes. Non-relational databases don’t need fixed table sachems. NoSQL databases are scaled horizontally and support limited join queries.

Incidentally, NoSQL is short for “Not Only SQL.”

Why MongoDB?

There are four major reasons why MongoDB is being deployed more often. They are:

1. Flexibility:

MongoDB uses documents that can contain sub-documents in complex hierarchies making it expressive and flexible. MongoDB can map objects from any programming language, ensuring easy implementation and maintenance.

2. Flexible Query Model:

The user can selectively index some parts of each document or a query based on regular expressions, ranges, or attribute values, and have as many properties per object as needed by the application layer.

3. Native Aggregation:

Native aggregation allows users to extract and transform data from the database. The data can either be loaded into a new format or exported to other data sources. 

4. Schema-less model:

Applications get the power and responsibility to interpret different properties found in a collection's documents. 

Salient Features of MongoDB


1. General-Purpose Database:

MongoDB can serve diverse sets of data and multiple purposes within a single application. 

2. Flexible Schema Design:

The document-oriented approach allows non-defined attributes to be modified on the fly. This is a key contrast between MongoDB and other relational databases. 

3. Load Balancing and Scalability:

It is built to scale, both vertically and horizontally. Using the technique of sharding, an architect can achieve both write and read scalability. Data balancing occurs automatically and transparently to the user by the shard balancer.

4. Aggregation Framework:

MongoDB offers an Extract, Transform, Load (ETL) framework which eliminates the need for complex data pipelines.

5. Native Replication:

Data gets replicated across a replica set without a complicated setup.

6. Security Features:

Authentication and authorization are taken into account. 

7. JSON:

JSON is widely used across for frontend and API communication. It only makes sense for the database to use the same protocol. 

8. MapReduce:

MongoDB offers a great tool, MapReduce to build data pipelines. 

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The Benefits of MongoDB

MongoDB brings a host of benefits to the table. Its advantages include:

  • NoSQL databases are cheaper and easier to maintain. NoSQL databases have features like easier data distribution, simpler data models, and automatic repair. These benefits require less administrative costs and, consequently, are less expensive.
  • It’s open-source and incurs fewer server costs. Open-source is free. NoSQL databases use cheaper servers, so the price of data storage and processing per gig is significantly lower.
  • It’s easily and highly scalable. Since NoSQL databases like MongoDB expand horizontally, you can scale by adding more machines to your resource pool.
  • It supports integrated caching. System memory caching boosts data output performance.
  • MongoDB has no schema hassles. You can place data into a NoSQL database without requiring a predefined schema, so you can change the data model and formats without disrupting applications.
  • It’s user-friendly. MongoDB offers plenty of useful features (Ad-hoc queries, aggregation, capped collection, file storage, indexing, load balancing, replication, server-side JavaScript execution) that makes it a user-friendly database.

When Should You Use MongoDB, and When Shouldn’t You?

Although MongoDB is a great database, there are times when you should and shouldn’t use it. It’s not universally applicable. Like any other tool, it has limitations.

MongoDB works best with unstructured data, so it’s great for Big Data systems, MapReduce applications, news site forums, and social networking applications. Use MongoDB when:

  • You’re using cloud computing. MongoDB is ideal for cloud computing. Cloud-based storage needs to easily distribute data across multiple servers, which suits MongoDB’s nature perfectly.
  • You need your data fast and easily accessible. Use MongoDB when you’re running performance-critical applications. MongoDB offers high data availability, providing instant and automatic data recovery.
  • You don’t have a database administrator. Perhaps you have a tiny business or are launching a start-up company, and you don’t yet have the resources to recruit a full-time Database Administrator. However, MongoDB is low maintenance, so the absence of an administrator won’t be as painful.
  • You have lots of unstructured data. MongoDB (and NoSQL databases in general) has no storable data type limits.
  • You’re using Agile methodologies for development. Relational databases are anything but agile, and they will slow you down. On the other hand, a database like MongoDB doesn’t require the level of preparation that its relational counterpart requires.
  • You have schema issues. If you have an unstable or undefined schema, use MongoDB.

However, MongoDB is not a cure-all. Here’s when you shouldn’t use a non-relational database.

  • You need ACID compliance. In this case, ACID is an acronym for Atomicity, Consistency, Isolation, and Durability. Applications that need database-level transactions (like for a financial institution’s core banking system) must be ACID compliant.
  • You work with stored procedures. Unfortunately, MongoDB has no provisions for stored procedures.
  • Your data is unchanging and structured. If your business isn’t undergoing explosive growth and its data stays consistent, there’s no need for a database like MongoDB.

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Working of MongoDB


The entire database consists of collections. These collections hold multiple documents, and since MongoDB is schemaless, the documents in one collection need not be similar. All data is stored as BSON documents with the help of key-value pairs. At the backend, MongoDB converts JSON data into a binary format known as BSON. MongoDB also makes provision for nested data. This makes fetching data comparatively efficient.  

MongoDB Applications

Several areas of technology use MongoDB as their Database Management System. 


Internet of Things (IoT), mobile applications, real-time analysis, personalization, catalog management, and content management, among others, readily deploy MongoDB. 

MongoDB vs MySQL

Let’s make a simple head-to-head comparison of these two popular databases.






High data security

Data Structure

Unstructured, or structured data that will potentially grow fast


Data Representation

JSON documents

Tables and rows

JOIN Support



Query Language


Structured Query Language (SQL)


No need to define

Must define columns and tables

Developer Productivity



Atomic Transactions

(e.g., having several operations within a transaction)

Doesn’t fully support all operations but supports multi-document transactions

Supports atomic transactions

MongoDB Examples

MongoDB has its fans, and here are a few examples of organizations or companies that use the database.

  • Aadhar. India’s Unique Identification project boasts the largest biometric database in the world. The Aadhar Project uses MongoDB to store the massive demographic and biometric data of over 1.2 billion Indians. Aadhar also uses MongoDB to store project images.
  • eBay. The popular online auction site uses MongoDB for projects such as cloud management, metadata storage, search suggestions, and merchandise categorization.
  • Shutterfly. This well-known Internet-based photo-sharing company has over 6 billion images and a transaction rate of up to 10,000 operations per second. Shutterfly moved from Oracle to MongoDB, as it found the non-relational database more suited to their needs.
  • Electronic Arts. EA uses MongoDB for FIFA Online 3, their popular online multiplayer game.


Companies like Toyota, Cisco, Verizon, Barclays, and Google among others are readily deploying MongoDB as the DBMS. 

Limitations of MongoDB

  1. MongoDB uses high memory for data storage.
  2. The BSON document size cannot exceed 16MB.
  3. Naming restrictions for databases in Windows.

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Ready to Tackle MongoDB and Kick Start Your Software Development Career?

As you can see, MongoDB is a huge hit in the IT world. Knowing how to leverage the tool when building applications and services can help you stand out from the crowd when looking for a new and hopefully better job. To learn how you can use MongoDB to jumpstart your software development career, look no further than Simplilearn, specifically our Caltech Post Graduate Program in Data Science would be helpful.

Delivered in collaboration with Caltech CTME, this comprehensive online boot camp will give you everything you need to become a full-stack web developer in just a few months. You will learn through over 250 hours of interactive applied learning, 20 lesson-end, and five phase-end projects, masterclasses from Caltech CTME faculty, a capstone project in four domains, and much more. What’s more, upon completion, you will receive a Post Graduate Certificate from Caltech CTME, up to 25 CEUs, Caltech CTME Circle Membership, and more. What are you waiting for?