Frameworks & Languages

Django vs FastAPI: Choosing a Python Web Framework

Django gives you a complete application with an admin panel. FastAPI gives you a fast, typed API and nothing else. The right answer depends on what you are building.

Python development with Django and FastAPI frameworks

Python's two dominant web frameworks are not really competitors — they solve different problems. Choosing between them is mostly a question of whether you need a complete application or a fast interface to one.

Django: Batteries Included

Django ships with an ORM, migrations, authentication, form handling, templating, security protections and — its stand-out feature — an automatic admin interface generated from your models. For internal tools, that admin alone can save weeks of work.

The trade-off is that Django has opinions. You work its way, with its ORM and its project structure. For most teams that is a benefit: two Django projects look alike, so developers move between them easily.

It suits content platforms, internal systems and data-backed applications where a usable admin is a requirement rather than a nice-to-have. We used Python development on this basis for a university faculty research portal, where staff needed to manage structured records without a bespoke interface being built for every model.

FastAPI: Fast and Typed

FastAPI does one job well: building APIs. It is async-first, validates requests through Python type hints, and generates interactive OpenAPI documentation automatically — which in practice ends arguments between frontend and backend developers about what an endpoint returns.

It is notably quick, both to run and to write. What it does not give you is an ORM, an admin, authentication or templating. You assemble those, typically with SQLAlchemy and a library of your choice.

Choosing Between Them

  • Need an admin interface? Django, almost automatically.
  • Building a pure API for a React or mobile front end? FastAPI.
  • Serving machine learning models? FastAPI — async handling and typed request bodies suit inference endpoints.
  • Traditional server-rendered pages? Django.
  • Many concurrent I/O-bound requests? FastAPI's async model has the edge.

Using both is perfectly reasonable: Django for the back office, FastAPI for high-throughput endpoints, sharing a database.

Why Python at All?

If the application is ordinary business software, Laravel will usually deliver it faster and host it more cheaply. Python earns its place when the work itself is Python-shaped: data processing, document handling, scientific computation, or anything touching machine learning.

That was the deciding factor in invoice processing with OCR automation — the document pipeline was the product, and the libraries for it exist in Python and nowhere comparable. The same logic applies to most AI integration work, as we set out in practical AI use cases.

Deployment Realities

Python web applications need a WSGI or ASGI server, a process manager and somewhere to run — more involved than dropping PHP files on a host. Dependency management deserves care, because Python environments drift. Containers solve most of this, at the cost of needing DevOps capability on the team.

Async is not a free speed increase either. A synchronous database driver inside an async endpoint blocks the event loop and can make performance worse than the framework you replaced.

A Sensible Default

If you are unsure, start with Django. The admin and built-in features carry a project a long way, and adding FastAPI endpoints later is straightforward. Starting with FastAPI and discovering you needed an admin means building one.

Whichever you choose, the database design will affect performance more than the framework, and a clean API contract matters more than either.

Tell us what the system needs to do and we will recommend the framework — and say plainly if Python is not the right language for it.

Frequently Asked Questions

Should I use Django or FastAPI for my project?

Use Django when you need a complete application with an admin interface, authentication, forms and server-rendered pages. Use FastAPI when you are building a pure API for a React or mobile front end, serving machine learning models or handling many concurrent I/O-bound requests. If you are unsure, Django is the safer default.

Can Django and FastAPI be used together?

Yes. A common setup uses Django for the back office and admin, and FastAPI for high-throughput API endpoints, with both sharing the same database. This keeps Django's built-in features for staff while giving external clients a fast, typed API with automatically generated documentation.

Is FastAPI faster than Django?

FastAPI is generally faster for API workloads because it is async-first and lightweight. That advantage disappears if you use a synchronous database driver inside async endpoints, which blocks the event loop. For most projects database design affects performance more than the choice of framework.

When is Python a better choice than PHP for a web application?

Python earns its place when the work itself is Python-shaped: document processing, data pipelines, scientific computation or anything involving machine learning, where its libraries have no close equivalent. For ordinary business software, Laravel will usually deliver faster and host more cheaply.

How We Can Help

Services Related to This Article

The work we do with the technologies discussed above — with pricing, process and real examples on each page.

  • Python, Django & FastAPI Development

    Python web applications and APIs built with Django, FastAPI or Flask — plus automation, data processing, OCR and document pipelines.

  • PHP & Laravel Development

    Laravel web applications, custom PHP development, admin panels, APIs and legacy PHP upgrades — secure, well-structured and easy to maintain.

  • AI Integration & LLM Development

    Practical AI in your product — assistants, document understanding, search over your own content, and OCR or classification pipelines built with Python and modern LLM APIs.

  • Cloud Hosting & DevOps

    AWS, Azure, Google Cloud and DigitalOcean setup, Docker and Kubernetes, CI/CD pipelines, Nginx tuning, monitoring, backups and cost optimisation.

In Practice

Case Studies on This Topic

Projects where we put these ideas to work, each with a live demo.

  • Accounting Finance — Ledgerline Accountants
    • Python
    • FastAPI
    • Tesseract OCR

    Data Automation & OCR

    Invoice Processing & OCR Automation

    A Python pipeline that reads 18,400 supplier documents a month and posts 93% of them without a person keying anything.

  • Man at a laptop in an office — Helm Software
    • Python
    • FastAPI
    • Vector database

    AI Integration

    Support Assistant Grounded in Product Documentation

    A retrieval-based assistant answering customer questions from the vendor’s own documentation, with citations.

  • Containers Bins — Stanmore Haulage
    • Azure Document Intelligence
    • Python
    • FastAPI

    Data Automation & OCR

    Proof-of-Delivery Capture with OCR for a Haulage Firm

    Photos of signed delivery notes turned into invoice-ready data automatically, cutting the gap between delivery and invoice from six days to one.

Keep Reading

Let’s Connect

Let’s Build Something Amazing Together

Share your project details and our experts will get back to you within one business day with the best solution — free consultation, no obligation.