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Aaron Gallant
Aaron Gallant
Data Science Curriculum Lead
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Every website collects user data, and the volume can be enormous. That's why it's crucial to have a database that manages this data effectively and quickly.

As a newbie, you can choose any database to learn from. But where should you start? Suppose you prefer something easy and convenient to work with. In that case, MongoDB might be a perfect match!

What is MongoDB?

MongoDB is a document-oriented database designed to store large-scale data. It means that it views database components as a set of interacting objects. A database is like a warehouse with plenty of goods. MongoDB and other database management systems work similarly to a chain of warehouses: they help to find the needed item and take it out for a client, input the new products, and organize the storage of all goods. A MongoDB server usually has multiple databases.

It is one of the most popular NoSQL (not only SQL) databases. They are different from traditional or SQL relational databases. SQL (Structured Query Language) is a programming language needed to manage relational databases with the four basic database operations: create, read, update, and delete (often referred to as CRUD).

SQL databases store data in tables, which have fixed sсhema. In a database with a fixed schema, new data must match the existing data type. For example, adding fractions to a database that contains only integers will result in an error. Instead, you should add only valid integer data.

Moreover, SQL databases usually require high-capacity hardware, if you need to scale them because the data can't be split. It also means that relational databases don't fit well to work with large amounts of data.

NoSQL databases store data in various ways: graphs, key-value pairs, documents, or columns. They don't use strict schema, so they stay easy to modify. MongoDB has collections and documents instead of tables and doesn't require a predetermined structure — you can store any amount of data and change the type of data anytime. It works like a note-taking app on your phone — you can add text, images, spreadsheets, and more to your notes.

That's why it's suited best for big data storage. It is flexible, easy to scale, learn, and work with.

What is MongoDB used for?

IT specialists in many industries choose these databases for their purposes: media, software, telecommunications, financial services, retail, healthcare, and more. Data developers and big data analysts use MongoDB while working with huge amounts of data, as well as backend and full-stack developers to create websites and applications.

Here are some of MongoDB's typical use cases:

  • Big data storage to store hierarchical relationships and large amounts of data
  • Social networking applications to scale out databases if the business grows and gets more traffic
  • Blogging platforms and forums
  • Real-time analytics & e-commerce applications
  • E-commerce product catalogs to update data in any database or document
  • Data Hub
  • Content Management and Content Delivery Systems (CMS and CDS) when you have a lot of unstructured data and undefined sсhema
  • Metadata storage
  • Cloud management to work with cloud-based storage
  • Gaming projects
  • Startups when your business is too young and small to have a database administrator

Companies like EA, eBay, and Google which need to collect and work with a big amount of user data rely on MongoDB. For example, Shutterfly uses it to store shared photos in separate databases, and thousands of them are managed every minute. This database is also the choice for working with complex data without pre-determined schema and projects which have been growing fast like Bingel, Sanoma Learning's app.

Why use MongoDB? Features and perks

Released in 2009, MongoDB is now one of the most popular NoSQL databases. There are thousands of MongoDB community members, students learning it, and professionals working with the database. Let's look closely at its key features and benefits.


Documents in the database don’t need to have a fixed schema and may be different from each other — there is no specific format we have to use to enter the data. Like different types of content in your note-taking app. Data with complex relationships can be in the same document and you can efficiently retrieve it without complex joins, that's why it's intuitive and fast to develop.


MongoDB allows you to make changes quickly and doesn't affect existing data because data is stored in documents, not tables. These documents are JSON-like — human-readable, lightweight, and based on JavaScript, and can be easily imported to Node.js or another system. You can customize databases as the application needs to change by rewriting a document, not the entire database. This makes the database management system more flexible and customizable.

Open-source and cross-platform

MongoDB is managed by MongoDB, Inc. under SSPL (Server Side Public License) and officially provides drivers for Python, Node.js, PHP, C, C++, and other popular languages. It could work under Linux, Windows, and Mac OS.


When the number of users increases, MongoDB databases could be easily split and scaled out to millions of documents across multiple existing servers. Although SQL databases are scalable nowadays, it requires a lot of complex work. In addition, if you need to store more and more data, to scale your SQL database up you have to add new, more expensive servers. This is the reason why MongoDB scaling is easier and much cheaper when you work with huge amounts of data.


Easier data replication through copies of data in multiple databases makes backup hassle-free. This vastly increases the reliability and security of data storage.

Ability to query

Allows you to make dynamic queries using a document-based query language that’s as good as SQL (without the necessity of learning SQL). To get the information you don't have to join separate tables — you can retrieve a single document. For example, get information about users' traffic source, region, visit date, and if they put a purchase in the cart. You may quickly find the needed data to create, read, update, or delete it. MongoDB querying helps provide high data performance and optimization making this database system easier to use.


Indexes are references in the document which allow searching for specific data. You may use a wide range of index types in any field. For example, the compound index can have both "Last name" and "First name" to efficiently query against any names. MongoDB provides an easier and faster search which assists in the work of analysts.

Easy to manage

MongoDB is user-friendly with a “human-understandable” language — you can work without a database administrator if you have a small business or startup. MongoDB features such as indexing, automatic repair, or simpler data modeling help a novice user perform complex actions and reduce costs.

Drawbacks and alternatives

Different databases could fit various business needs and aims. Some companies choose both SQL and NoSQL databases for specific tasks or analyze which database will be the match. 

MongoDB has some disadvantages to consider:

  • Can't provide high levels of data accuracy and consistency, for example, for financial transactions
  • It is essential to have a lot of memory to store the data
  • You can't store over 16MB of data in the document
  • Data nesting restrictions — each object adds a level deep, in MongoDB data can't be nested more than 100 layers deep
  • Naming restrictions — the names of databases should be different, but they can't contain some characters, be more than 64 characters, or be empty, also there are naming restrictions for collection, fields, etc. which you should remember about
  • Types of data should be considered in advance, even without a fixed schema: it matters when you need to read the data

Relational databases like MySQL are traditional — well-tested, stable, compatible with a majority of languages and platforms, have a lot of information to learn with a huge community, and support transactions natively, while MongoDB can't provide plenty of them without issues.

Also, you may select one of the other NoSQL databases as an alternative. Some of the most popular and reliable include: 

  • Redis — a key-value database that stores data in memory allowing management data very fast and saving it to disk. But it's expensive to scale, and as a result is usually used for cashing.
  • Apache Cassandra — database system designed to store and manage huge amounts of data across multiple servers. It is known for its ability to handle large amounts of data while being reliable and available in the event of hardware failures. It organizes data in a way that makes it easy to retrieve and manage. It can be expanded by adding more servers to the system.
  • Amazon DynamoDB — a key-value pair database created by Amazon that can handle a large number of requests, not an open-source one.
  • Neo4j — a graph database stores and quickly manages data in a connected way, visually representing billions of relationships in a single graph, providing deeper context for data analysis.

How to start learning MongoDB

MongoDB is a user-friendly database, so it’s a great entry point in databases. It is easy to install, set up, and work with. 

Unlike relative databases, you don't need to be a high-level expert to start exploring MongoDB. Since it’s a NoSQL database, you don't have to know SQL. You can work with MongoDB using JavaScript or any other major programming languages. 

You may get to study it in the MongoDB free learning platform with video lessons, labs, and certification. Choose the programming language (C#, Java, Python, etc.), take the course that suits you, and get the certificate. Also, you may take one of the 3-12 hours of introductory courses to learn the basics. 

The MongoDB website could become a great resource for getting to know this database. However, there are other MongoDB resources available. For example, you can look at TripleTen's Software Engineering Bootcamp. This all-in-one solution gives you the knowledge and skills you need for your development journey. You will learn MongoDB and other tools for the frontend and backend of your full-stack developer career.

Another way to jumpstart your development career is offline bootcamps or courses. They’re great choices to get some practice and concentrate on the studying process and finding like-minded people.

In general, it will take you about three weeks to get going in MongoDB. The timing depends on your previous knowledge. To make it easier for you, you can start by learning programming languages such as JavaScript, Python, and others. You can read more about them on our blog.

Eventually, if you get a certificate, it can be a milestone that helps you to find the job you always wanted! 

Boosting your skill to an expert level can raise your salary and open new career opportunities. With relevant work experience and portfolio, you could become a software developer or a full-stack developer in demand. Another option is to grow like a multi-skilled professional in the field of data analytics as a big data developer, adding the MongoDB framework as one of the competitive skills. 

If you have chosen to become a database administrator or system architect, high-level MongoDB knowledge would be one of your core competencies. 

Summing it up

MongoDB meets the requirements of modern applications: ensures high response time, makes system maintenance and searching easier, and lower operational costs with horizontal scaling.

MongoDB allows you to store a large amount of data without a fixed structure and manages it efficiently and quickly. As a result, it is one of the most used databases, chosen by the top companies, and its popularity is growing.

This NoSQL document-based database is definitely worth the time you spend studying it. If you set MongoDB as your learning goal, it will help you to step up in your IT career, wherever challenging and up-to-date projects you wish to work with, and be more marketable.

It is free, user-friendly, compatible with the most popular languages and platforms, and has a short learning curve, so you may use your competencies as a base and find yourself at a new level of proficiency and financial perspectives!

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