This article is written by Anaiya Raisinghani (Developer Advocate @ MongoDB)
Those who are familiar with Django know how easy it is to create complex applications with just a few lines of code, but what happens when an application suddenly needs to scale? Or if it becomes necessary to incorporate vector search queries to stay ahead of competitors? Or if an application needs massive structural changes but can’t afford the downtime? For years, Django and relational databases have been a trustworthy pair, but let’s change things up and enter into a new era: Django with a document database like MongoDB.
There are a multitude of benefits of using a NoSQL database like MongoDB while building complex applications with Django. Let’s go over some of them.
Let’s cover our basics…
What is a NoSQL database?
A non-relational database is what’s most commonly referred to as a NoSQL database. This has to do with how data is stored inside the database—a non-relational database stores data in a non-tabular format and can be described as more flexible than a traditional, SQL-based relational database. How does this format make it more flexible? Take MongoDB’s document model approach as an example: Data is stored as documents, and these documents store data in a JSON format with a flexible schema. This flexibility allows MongoDB to effectively store and manage structured, semi-structured, and unstructured data, a capability where traditional relational databases often fall short. This key advantage to NoSQL databases allows for constant evolving and adaptation when working with data, since they support diverse data models and changing data requirements.
What is Django?
Django is a Python web framework known for helping developers build web applications as quickly as possible, while keeping development clean and maintainable. It’s especially known for its “batteries included” design—a way to implement a multitude of standard webserver capabilities through various mechanisms that developers need to build their applications, making it so developers don’t need to code crucial steps from scratch! Some of these mechanisms are: generating frontend HTML, handling session management, managing database connections, and handling route resolution.
Many of these mechanisms listed have a typical SQL back end, but what if these commonly used callbacks were replaced with MongoDB’s querying syntax? Keep reading to understand the benefits of using a NoSQL database with Django, and the incredible possibilities available for developers.
An overview of Django-MongoDB-Backend and the launch
Our library, django-mongodb-backend, is a third-party database back end that integrates seamlessly with Django. When a developer defines the database backend engine when creating their application, they can go ahead and specify a custom back end—such as django_mongodb_backend. As long as django-mongodb-backend is installed in your Python environment, Django will connect without issues.
django-mongodb-backend aligns with the familiar steps Django developers know and love. This process is smooth, particularly because MongoDB is determined to support as much of Django’s core features as possible. Some of these features include programmatic database connectivity in settings, representing MongoDB documents through Django models, querying data through the Django QuerySet API, the Django admin panel, etc.
Now that we’re familiar with the purpose of our library, let’s get into why developers should try it out.
Key benefits of using MongoDB with Django
- MongoDB's document model
- Data platform capability with MongoDB Atlas:
- Deploy anywhere, build and scale quickly without the hassle of managing infrastructure
- World class security/encryption
- Atlas Search
- Advanced search and AI capabilities right out of the box:
- Leverage our native AI integrations for most popular AI frameworks such as LangChain, LlamaIndex, and Haystack
- Vector Search
- Aggregation framework:
- Leverage MongoDB's powerful aggregation framework to perform complex queries and generate real-time analytics
- Robust ecosystem of tools to provide world class developer experience
MongoDB’s document model
MongoDB’s document model is what sets it apart from other databases, but at its core, it aligns particularly well with Django’s proud mission—to ensure fast development while keeping the overall design clean. It truly is a natural fit for Django developers because it allows an intuitive way to map Django models to MongoDB documents, as the document model is all about storing and retrieving your data in a way that developers already think and work. MongoDB will allow for Django developers to create their models in a whole different way—developers won’t need to utilize JOINs in various use cases, as data that is accessed together should be stored together.
Just as Django is known for its rapid development and simplistic design, MongoDB truly simplifies data modeling. Hand in hand, with Django as the framework and MongoDB as the database, developers can focus on building full, complex applications instead of struggling with creating everything from scratch. The great advantage with this pair is developers can deal with any hierarchical data, semi-structured data, or rapidly evolving data, and MongoDB will store it in a way that feels natural.
Data platform capability
MongoDB isn’t just limited to how data is stored. With MongoDB Atlas, developers can help make managing data seamless through incredible features like Atlas Search for full-text and vector search capabilities. For more complex applications, MongoDB’s aggregation framework helps developers with difficult queries, transformations, and various analytics, directly on their data.
For a local project, creating an Atlas deployment using Docker is easier than ever! Developers can spin up a single-node replica set by pulling the Docker image and running it with an Atlas connection string. Already have an existing Atlas implementation? No worries, it’s possible to convert that into a local image if it’s running in Docker Compose. All developers need are the Atlas CLI and Docker to create with Django and MongoDB.
Developers can also feel fully confident in the security of their data with MongoDB. Our platform offers incredible encryption features, ensuring data is protected in transit, at rest, and in use. With client-side field-level encryption and queryable encryption, a developer's data protection needs will be fully accounted for throughout the entire data lifecycle.
With the flexibility of the document model, the power of MongoDB’s expansive data platform, and advanced tools, developers can truly build incredible applications.
Advanced search and AI capabilities
It’s crucial to stay competitive. MongoDB makes it easy to build incredibly powerful and competitive artificial intelligence applications. With our seamless integrations with frameworks like LangChain, LlamaIndex, and Haystack, developers can stay ahead of the game and build AI-powered chatbots, personalized recommendation engines, and so much more.
Our search capabilities are not isolated to full-text search. MongoDB covers all vector search and hybrid search needs. With MongoDB’s full-featured vector database capabilities, developers can truly stay ahead of the game by enabling intelligent semantic search over any kind of unstructured data, whether that is text, images, or audio. The opportunity to explore the combined power of vectors, MongoDB, and Django is truly only one pip install away.
For applications that require real-time data, MongoDB is meant to help deliver speed, scalability, and reliability. From instant data retrieval, to supporting high-performance applications with no required downtime, applications are built to stay responsive and ready to meet modern demands. The intersection of MongoDB and Django can truly raise the bar: Developers will have the flexibility and scalability of a NoSQL database while greatly benefiting from Django’s development framework.
Aggregation framework
Have a Django application with a lot of data and want to receive computed results from various records? The MongoDB aggregation framework can help. By using the built-in operators available, developers are able to do various complex analytics on servers that are already in use—no need to incorporate a third-party platform. The aggregation pipeline in MongoDB allows for robust data transformation and consolidated results from any collection of data.
Robust ecosystem of tools
MongoDB allows for Django developers to build how, when, and wherever they need, whether it’s with the open-source MongoDB Community or the fully managed MongoDB Atlas platform. There truly is a deployment option available for every developer, such as those who are trying a new project on the side with our free cloud database cluster, or those interested in creating enterprise-grade solutions.
Storing and querying data is just the tip of the iceberg when it comes to building applications. MongoDB offers a robust ecosystem of tools that are specifically designed to help enrich the development experience and truly simplify interactions with data. Whether a developer is working in VS Code with the MongoDB extension, using JetBrain’s Database Tools in PyCharm, or coding with the MongoDB Shell and Atlas CLI, MongoDB has everything you need to interact with your data. And for those developers who prefer a more intuitive database experience, MongoDB Compass is the answer. With tools like mongoimport and mongoexport, data management is incredibly simple, as well.
When a developer works with MongoDB, they are not just working with a database—they are working with a robust ecosystem of tools designed to enhance the entire development process from start to finish.
Best practices for implementing NoSQL with Django
To get started with using our django-mongodb-backend library, please check out our GitHub repo and our Quickstart for further direction.
Conclusion
This integration between Django and MongoDB is what developers need! The combination of MongoDB’s document model, vast ecosystem of tools, and advanced features like Atlas Search and AI integrations allows for Django developers to build complicated apps, simply. With the django-mongodb-backend library, integrating a NoSQL database into a Django project has never been easier. Everything is fully taken care of in the back end so Django developers can still use the same commands they’re used to, allowing for an easy transition from a relational to a non-relational database. Please keep in mind that our integration is currently in Public Preview and is only recommended for testing purposes.
Try it out for yourself today and let us know your thoughts in our Developer Forum!
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