In this article, we’ll be learning about 3 different platforms and their key features and mainly focussing on MongoDB with Python Django

Python, the most popular programming language for data science, has always worked well with MongoDB to create powerful applications. Django, the most popular Python web framework, is an excellent tool for developing secure and easy-to-maintain MongoDB applications.

Consider the following scenario: you are working on a real-time project. The data you’re working with is unstructured and contains millions of records. This is where MongoDB comes into play. It has the ability to store unstructured data and provide easy access to it.

Now that we have a basic understanding, let’s dig a little deeper into MongoDB with Python Django Connection.


  • Python 3.6 or higher is required.
  • MongoDB version 3.4 or higher. (If you’re using nested queries, you’ll need MongoDB 3.6 or higher.)

What is MongoDB?

MongoDB with Python Django - MongoDB logo
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MongoDB is a well-known C++-based open-source NoSQL database. MongoDB is a Document-Oriented Database that stores data in JSON-like documents with a Dynamic Schema. It means you don’t have to worry about the Data Structure, the number of fields or the types of fields used to store values when storing your records. MongoDB documents are similar to JSON objects.

You can change the structure of records (referred to as Documents by MongoDB) by simply adding new fields or deleting existing ones. This MongoDB feature makes it simple to represent Hierarchical Relationships, Store Arrays, and other more complex Data Structures. Many tech behemoths, including Facebook, eBay, Adobe, and Google, now use MongoDB to store massive amounts of data.

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Key Features of MongoDB

MongoDB has a number of distinguishing features that make it a superior solution when compared to other traditional databases. Some of these characteristics are discussed further below:

  • Database with Fewer Schemas: A Schema-Less Database enables the storage of various types of Documents in a single Collection (the equivalent of a table). In other words, a single collection in the MongoDB database can hold multiple Documents, each of which can have a different number of Fields, Content, and Size. MongoDB provides users with a lot of flexibility because of this feature.
  • Document with an Index: Every field in a MongoDB Database Document is indexed with Primary and Secondary Indices, making it easier to retrieve information from the pool of data.
  • Scalability: In MongoDB, sharding allows for horizontal scalability. The process of distributing data across multiple servers is referred to as sharding. Using the Shard Key, a large amount of data is partitioned into data chunks, and these data chunks are evenly distributed across Shards that span many Physical Servers.
  • Replication: MongoDB provides high data availability by making multiple copies of the data and sending these copies to different servers so that if one server fails, the data can still be retrieved from another.

What is Python?

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Python is a high-level, general-purpose programming language that is open-source and has dynamic semantics. Guido Von Rossum created it in 1991 to improve code readability through indentation. It is garbage-collected and dynamically typed. Python includes modules and packages that promote program modularity and code reuse.

What is Django?

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Django is a Python Web Framework that is free and open-source, and it uses the Model–Template–Views architectural paradigm. Its upkeep is the responsibility of the Django Software Foundation, a non-profit organization based in the United States. Django enables you to create a high-quality Web application quickly and easily. It can be used for both frontend and backend development.

Django follows strong design principles throughout its code and makes it easy to implement top web-development techniques. Instagram, Disqus, Washington Times, Bitbucket, and Mozilla are just a few of the well-known platforms that use Django. This Framework connects the Data Model to the Database Engine and supports a wide range of databases. Django’s philosophy is to do everything possible to allow for hyper-fast development.

Key Features of Django

Let’s take a look at some of Django’s features that make it a popular choice among Python developers:

  • Secure: Django has been designed to “Do the Right Things” automatically in order to protect the website. Django avoids common pitfalls such as storing session information in cookies, which is a security risk. SQL injection, cross-site scripting, and cross-site request forgery are all vulnerabilities that Django automatically protects against.
  • Scalable: Django uses a “Shared-Nothing” architecture, which means that each component of the architecture is independent of the others. Because the various components are clearly separated, they can be scaled to meet increased demand by adding hardware at any level.
  • Maintainable: Django code is written with design principles and patterns in mind, which results in code that is simple to maintain and reuse. It applies the “Don’t Repeat Yourself” (DRY) principle to eliminate unnecessary repetition and thus reduce the amount of code.
  • Versatile: Django can be used to build almost any type of website, from content management systems and wikis to social networks and news sites.
  • Portable: Django is written in Python, a programming language that is cross-platform. That means you’re not tied to a single server platform and can run your apps on Linux, Windows, and Mac OS X. Django is also well-supported by a large number of web hosting providers, which frequently provide dedicated infrastructure and documentation for hosting Django sites.
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Django Methods for Connecting to MongoDB

Django can be linked to MongoDB in three ways:

MongoDB with Python Django - Django Methods for Connecting to MongoDB
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MongoDB with Python Django Connection: PyMongo

PyMongo is the standard driver that allows MongoDB to communicate with Django. It is the official and preferred method of interacting with MongoDB in Python. PyMongo has the ability to perform all database operations such as search, delete, update, and insert. Because PyMongo is included with PyPI, you can quickly install it with the pip command.

PyMongo is a very efficient way of writing JSON data to MongoDB and allows you to use MongoDB queries directly in your Python code. Using PyMongo, we can retrieve data in a dictionary-like syntax.

PyMongo can be easily installed with the pip/pip3 command:

pip install pymongo[snappy,gssapi,srv,tls]

If you are using a virtual environment (which you should be! ), you must install pymongo in the..venvLibsite-packages folder.

Install dnspython as well to use mongodb+srv:/ URIs with the command:

pip install dnspython

Using PyMongo, we can concurrently run multiple databases by specifying the right database name to the connection instance.

MongoDB with Python Django Connection: MongoEngine

MongoEngine is a Python Object-Document-Mapper. It’s similar to Object-Relational-Mapper in relational databases. MongoEngine has a declarative API that is easy to learn and use.

MongoEngine is an ORM layer that sits atop PyMongo. To use MongoEngine, you must still have PyMongo (>=3.4) installed on your system.

When you use MongoEngine to connect Django and MongoDB, you get fields like ListField and DictField to handle large amounts of unstructured JSON data.

First, install MongoEngine by going to:

pip install mongoengine

As we saw in the previous section, we must comment on the DATABASES section of when using PyMongo. Then, in order to use MongoEngine, include the following:

import mongoengine
mongoengine.connect(db=db_name, host=hostname, username=username, password=pwd)

With MongoEngine, we must define a schema in the Django application’s file. MongoDB has no schema. The schema is only enforced until the application level, making future changes quick and simple.

MongoDB with Python Django Connection: Djongo

If you are currently using a relational database such as SQL and want to migrate to MongoDB, you can do so with Djongo. Djongo transpires all SQL queries to MongoDB syntax queries without changing the Django ORM.

Djongo is superior to PyMongo in that developers do not need to write lengthy queries. It performs Object Document Mapping by mapping Python objects to MongoDB documents (ODM). Djongo makes certain that only clean data is entered into the database. There is no need to modify the existing Django ORM by performing integrity checks, applying validations, and so on with Djongo.

Install Djongo as follows:

pip install djongo

Now, open the file in your project folder (for example, MyFirstDjangoProj). Textpad, Python IDE, or any other editor can be used to edit it. Change the settings for DATABASES to point to MongoDB. The ENGINE is djongo, and the database name (NAME) is the name of your MongoDB database.

       'default': {
           'ENGINE': 'djongo',
           'NAME': 'db-name',

Then execute

python3 migrate

Key Notes for MongoDB with Python Django Connection

Now that we’ve learned about the various ways to connect MongoDB with Python Django Connection, we must select the best one for our project. Each method has advantages and disadvantages.

For example, if you’re starting from scratch, MongoEngine is a good choice because it can handle a large amount of unstructured data. If you need to write a lot of complex queries in your application, PyMongo is the way to go.

If you have a Django project that needs to migrate to MongoDB from another database, Djongo is the best option because it requires the least amount of code changes.


In this article, we will look at what MongoDB is, what Django is, and how to connect MongoDB with Python Django. I hope you now have a better understanding of the topics discussed above.

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Share with us your experience of MongoDB with Python Django Connection in the comments below!

Former Research Analyst, Hevo Data

Davor is a data analyst at heart with a passion for data, software architecture, and writing technical content. He has experience writing more than 100 articles on data integration and infrastructure.

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