FastAPI vs Django, and which suits your project

Choose FastAPI when you are building an API for a separate frontend, such as React or a mobile app, and want something small, typed and async from the start. Choose Django when you want a full web framework with an ORM, migrations, authentication, forms and an admin panel already included and wired together. FastAPI gives you a sharp tool; Django gives you a whole workshop.

Versions on PyPI as of 25 October 2026: fastapi 0.162.0 (released 23 October, Python 3.10 or newer) and Django 6.1.2 (released 6 October, Python 3.12 or newer).

Which to pick

• API-first project with a React, Vue or mobile frontend: FastAPI.
• Content-heavy site, marketplace or SaaS where you want admin screens on day one: Django.
• Team that needs one opinionated way to do everything: Django.
• Lots of calls to outside services and AI models per request: FastAPI, for its async-first design.
• You want a big, long-established ecosystem of reusable apps: Django.
• Small service inside a bigger system: FastAPI.

Philosophy

Django, first released in 2005, calls itself "the web framework for perfectionists with deadlines". It is batteries included: an ORM, a migration system, user accounts and permissions, sessions, forms, templates, an admin site, security middleware and more, all designed together. You follow its project layout and conventions, and in return a lot of decisions are made for you.

FastAPI, first released in 2018, does one job: turn typed Python functions into a fast, documented API. It brings validation through Pydantic, dependency injection and automatic OpenAPI docs. For the database, auth and admin you choose libraries yourself, such as SQLAlchemy or SQLModel, Alembic and an auth library of your choice.

Neither approach is better in general. Django saves time when its defaults match your project, and FastAPI saves time when they would not.

Code side by side

A small endpoint that lists published articles as JSON.

FastAPI with SQLModel:

from fastapi import FastAPI
from sqlmodel import Field, Session, SQLModel, create_engine, select


class Article(SQLModel, table=True):
    id: int | None = Field(default=None, primary_key=True)
    title: str
    published: bool = False


engine = create_engine("sqlite:///app.db")
SQLModel.metadata.create_all(engine)
app = FastAPI()


@app.get("/articles")
def list_articles() -> list[Article]:
    with Session(engine) as session:
        return session.exec(select(Article).where(Article.published)).all()

Django, with the model in models.py and a view in views.py:

from django.db import models
from django.http import JsonResponse


class Article(models.Model):
    title = models.CharField(max_length=200)
    published = models.BooleanField(default=False)


def list_articles(request):
    rows = Article.objects.filter(published=True).values("id", "title")
    return JsonResponse(list(rows), safe=False)

The Django code is shorter here, but it sits inside a project with settings, an installed app, a URL configuration and migrations created by manage.py makemigrations. The FastAPI file runs on its own. For serious APIs, Django projects usually add Django REST Framework or Django Ninja for serializers, validation and docs.

ORM and admin

This is Django's biggest advantage. Define models once and you get migrations, a powerful query API and an admin site where staff can browse, search and edit data, with permissions, after a few lines of registration. For many businesses the admin alone saves weeks.

FastAPI has no ORM or admin of its own. You pick an ORM, usually SQLAlchemy or SQLModel, add Alembic for migrations, and either build admin screens or add a third-party admin package. That is more setup, and also more freedom: you can use any database library, or none.

Async

FastAPI is ASGI-native. Endpoints can be async def, and a single process can serve many requests that are waiting on databases or network calls at the same time. That suits apps that call AI models, payment providers or other APIs on almost every request.

Django has supported async views since version 3.1 and runs under ASGI servers, and its ORM has gained async query methods over recent releases. Large parts of the ecosystem are still written for sync code, though, so an async Django project takes more care about which libraries you use. If async is central to your app, FastAPI gives you fewer surprises.

Security defaults

Django ships many protections switched on: CSRF tokens for forms, protection against SQL injection through the ORM, clickjacking headers, password hashing and secure session handling. You have to work to turn them off.

FastAPI gives you the building blocks, such as security schemes for OAuth2 and API keys, but you assemble login, sessions and permissions yourself or from libraries. That is fine for experienced teams and a risk for rushed ones. Whichever you pick, test that private endpoints refuse anonymous requests.

When to use each

Use Django for:

• Content sites, publishing tools and marketplaces with many data types.
• Products where non-technical staff need to manage data through an admin.
• Teams that value convention, long-term support releases and one way to do things.
• Server-rendered pages with forms, where Django's templates and forms shine.

Use FastAPI for:

• APIs behind a single-page app or mobile app.
• Services that call machine learning models or many external APIs.
• Microservices and small focused backends.
• Projects where you want typed request and response models and automatic docs.

What each choice costs over time

The first week is not where frameworks differ most. The difference shows up over a year of changes.

With Django, upgrades follow a predictable release cycle with long-term support versions, and the framework's pieces are upgraded together. The trade-off is that the project grows around Django's conventions. Moving part of it elsewhere later means untangling models, views and settings that assume each other.

With FastAPI, you own the integration between your chosen libraries. Upgrading SQLAlchemy, Pydantic and your auth library is your job, and occasionally one moves faster than the others. In return, each part is replaceable. Swapping the database layer or splitting a service out is usually easier because nothing was built around a single framework's assumptions.

Hiring is similar for both. Django has a long history and a large pool of experienced developers. FastAPI is newer, but any developer who knows modern typed Python picks it up quickly.

Hosting costs are close. Both run on any host that runs Python, in small containers or on a basic virtual server. Django apps often need a little more memory because they load more of the framework; for most small projects that difference is not worth choosing over.

A simple rule: if you can list five Django features you will definitely use, such as the admin, auth, forms, sessions and migrations, Django will repay its learning curve. If you mostly need endpoints that move JSON in and out, FastAPI keeps the project lighter.

Which one AI app builders choose

Most AI app builders that use Python, VibeDream included, choose FastAPI. Every VibeDream app has a React frontend and a FastAPI backend. A small, explicit backend is easier for an AI to change safely, validation errors are specific enough for an AI to fix, and the JSON API pairs cleanly with React. Because you can read every file, download a ZIP or sync to GitHub, a Django developer could still port the backend later if a project grows into Django's strengths.