How to Use Django With MongoDB

Django is a popular Python web framework for building secure, maintainable web applications. MongoDB is a flexible NoSQL database that stores JSON data in documents instead of tables. Using it with MongoDB combines Django’s development efficiency with MongoDB’s scalability and schema flexibility.

While traditional relational databases like PostgreSQL and MySQL work well for structured data, a non-relational database like MongoDB offers flexibility, horizontal scalability, and faster performance for modern, data-heavy applications.

For supported Django, Python, and MongoDB versions, see the compatibility table.

Important: Your backend version must match your Django version. For example, version 5.2 works with Django 5.2, and version 5.1 works with Django 5.1.

The backend works seamlessly with current MongoDB Atlas deployments.

Yes. It works with the backend, allowing you to manage your MongoDB collections directly from the admin dashboard. Once your database engine is configured, you can perform CRUD operations just as you would with a relational database.

Yes. You still use Django migrations to keep models and collections in sync. When you run “makemigrations” or “migrate,” it automatically applies schema changes to collections instead of SQL tables.

Indexes are created on collections instead of tables. You can define them in your model’s “Meta.indexes” setting, and the backend applies them during migration. For advanced search, MongoDB Atlas Search and text indexes are supported.

Yes. You can migrate records from PostgreSQL, MySQL, and SQLite by exporting your data, adjusting your Django models, and updating your database configuration to point to MongoDB.

This is a common step when moving from SQL to NoSQL systems.

Absolutely. When you deploy on Atlas, you can use global clusters, automatic sharding, and built-in backup and monitoring tools. This makes MongoDB Atlas ideal for Django projects that expect rapid growth or require multi-region performance.

No. It doesn’t use joins like SQL, but it offers similar functionality through aggregation pipelines and “$lookup” stages. With the official backend, these features are available through ORM methods, so you can run complex MongoDB query documents without writing manual database code.

Yes. The backend is fully supported and designed for production workloads. It integrates with Django’s built-in auth, sessions, and contrib modules, providing the same reliability expected from traditional database backends.

While MongoDB offers schema flexibility and fast writes, Django’s ORM was originally built for SQL systems. Some features, like foreign keys, complex joins, and strict constraints, function differently or require code-level adjustments.

The payoff is faster iteration and scalability for modern apps, but it may require rethinking how you model and validate input.

Yes. You can use multiple databases in a single project. Some models can be stored in PostgreSQL, while others use MongoDB collections. You’ll define multiple entries in your DATABASES setting and route models accordingly.

This hybrid approach offers flexibility but also increases management complexity.

All core features, including forms, authentication, sessions, and the admin interface,  work with the official backend. You can continue to use Django’s “contrib.auth” and admin tools while storing data in MongoDB collections.