Django vs FastAPI: Which to Pick (and When to Use Both)

For Django vs FastAPI, I pick Django when the application needs admin, ORM, auth and migrations out of the box. I pick FastAPI when I’m building an async, typed API. The question isn’t which framework wins a benchmark; it’s which work you want the framework to own.

My default for a product that genuinely needs both shapes is Django for the application’s internal machinery, FastAPI for external API routes. That is not my default for a new project with no clear split: operating one framework is a better starting point than designing an integration you might never need.

Django vs FastAPI: the short answer

Start with Django for an application; start with FastAPI for an API. Django’s models, views and templates give you a connected web-application stack, while FastAPI is built around Python type hints for API endpoints. Decide what you are shipping before deciding how much framework you want.

The exception is a product with separate internal and external needs. In our Django, FastAPI and Next.js stack, Django owns admin, ORM, authentication and migrations; FastAPI owns external API routes. That split is useful when you can name what each side owns without hesitating.

Don’t adopt both as insurance against choosing wrong. If the first release is mostly staff-managed data and customer accounts, the internal application is the architecture. If its defining surface is an external API, design that contract first. A second framework should solve a named problem, not a hypothetical one.

Django vs FastAPI at a glance

The meaningful difference is scope: Django supplies more of the application; FastAPI supplies the typed API layer and asks you to choose more of the surrounding stack. Read the table as a list of decisions your team will have to make, not a feature scorecard.

Concern	Django	FastAPI
Scope	Models, views and templates in one framework	API framework built on Starlette and Pydantic
Request model (WSGI/ASGI)	ASGI adapter and async views; ORM synchronous by default	ASGI-native; supports async def routes
ORM and migrations	Django models and migrations	No built-in migrations; commonly SQLAlchemy with Alembic
Admin	Django admin	Not part of the FastAPI stack described here
Auth	Django auth and sessions	Security schemes and dependencies; choose your user and token implementation
Validation	Add DRF serializers for API work	Type hints and Pydantic for requests and responses
API docs	DRF offers a browsable API	OpenAPI, Swagger UI and ReDoc
Learning curve	Learn the integrated application stack	Learn a smaller API surface, then choose the missing pieces
Best fit	Admin-heavy application and CRUD	Typed, async, API-first service

The learning-curve row is deliberately a judgement about what you learn, not a claim that one framework takes fewer days. Familiarity with Python types helps with FastAPI, but it does not make database and auth decisions disappear.

Philosophy: a full web framework vs an API toolkit

The Django documentation describes models for data, views for requests and templates for rendering. Those pieces give a server-rendered application a coherent starting structure.

The FastAPI documentation names Starlette for the web parts and Pydantic for the data parts. Standard Python type declarations describe inputs; FastAPI uses those declarations for validation. That is a strong default when the route contract is the centre of the product.

The freedom has a price: choose an ORM, decide who changes the schema, and define how users authenticate. For another API-framework comparison, see our FastAPI vs Flask decision framework.

Performance and async: what actually matters

FastAPI is a good choice for async, I/O-bound API routes; it is not a shortcut around blocking code. FastAPI is ASGI-native, and its documentation recommends async def when your code uses async and await. An endpoint that waits on an async dependency fits that model; an endpoint that calls a synchronous database client inside the event loop does not.

FastAPI’s performance claim places it on par with NodeJS and Go, attributing that performance to Starlette and Pydantic. Treat that as a statement about the framework, not a latency estimate for your product. If you do not know whether request handling or something behind it is limiting your service, measure that before replacing the framework.

Django is not devoid of async support. Its 4.1 release notes document async class-based view handlers and a-prefixed QuerySet operations such as aget(). Those same release notes say the underlying database operations at that stage remained synchronous and were wrapped with sync_to_async(); don’t read an async method name as proof of an async database driver.

The sharp edge in a mixed stack is specific: a direct Django ORM call inside a FastAPI async def handler blocks the event loop. Our stack guide gives two ways around it: wrap that call with sync_to_async, or make the FastAPI handler a plain def. Pick based on the actual data-access path, not on whether async looks more modern.

Data layer: Django ORM and migrations vs SQLAlchemy and Alembic

Choose Django’s data layer when you want models and schema changes under one framework’s control. Django’s migration system records state in migration files and django_migrations; our shared-schema guide warns that it assumes ownership of the schema. That assumption is useful for a single-owner application and dangerous when a second migration tool changes the same tables.

FastAPI does not include migrations. A FastAPI project commonly pairs SQLAlchemy with Alembic, so you must wire up models, database access and migrations rather than getting that combination from the API framework. If you want async database access, make the engine, driver and session lifecycle an explicit design decision.

That setup cost is justified when the API’s data access needs its own shape. It is harder to justify if every endpoint is ordinary CRUD over the tables Django already administers. For the async route, our FastAPI and SQLAlchemy session patterns cover engine creation, request-scoped sessions and transaction ownership.

Building APIs: DRF serializers vs Pydantic and automatic OpenAPI

Use Django REST Framework (DRF) when the API belongs to your Django application; use FastAPI when the typed API contract is the main event. DRF supports serialization for ORM and non-ORM data and provides a browsable API. Our configuration guide also notes that Django and DRF take more explicit serializer and routing setup than FastAPI.

FastAPI uses type hints for request and response validation and generates OpenAPI documentation. Its default interactive interfaces are Swagger UI and ReDoc; the OpenAPI schema can also support client generation. That combination matters when another team or a mobile client consumes the API and needs a contract it can inspect.

For example, here are two runnable versions of a small item endpoint. They demonstrate the API boundary, not a database-backed application: the DRF example declares a serializer, while the FastAPI example declares a Pydantic model and uses it as the request and response contract.

# Django project: add 'rest_framework' to INSTALLED_APPS.
# In an app's views.py:
from rest_framework import serializers, status
from rest_framework.decorators import api_view
from rest_framework.response import Response

class ItemSerializer(serializers.Serializer):
    name = serializers.CharField()

@api_view(["POST"])
def create_item(request):
    serializer = ItemSerializer(data=request.data)
    serializer.is_valid(raise_exception=True)
    return Response(serializer.validated_data, status=status.HTTP_201_CREATED)

# In that app's urls.py:
from django.urls import path
from .views import create_item

urlpatterns = [path("items/", create_item)]

# Save as main.py; run: uvicorn main:app --reload
from fastapi import FastAPI, status
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    name: str

@app.post("/items/", response_model=Item, status_code=status.HTTP_201_CREATED)
def create_item(item: Item) -> Item:
    return item

Neither example persists an item. That omission is the point: the route syntax is the cheap part of this decision. Decide who owns validation, schema changes and authentication before treating the shorter endpoint as the shorter application.

Admin, auth and the batteries you would otherwise build

Django is the stronger starting point when staff administration and user accounts are central to the product. Our Django–FastAPI architecture assigns the admin interface and authentication to Django. That lets the same application own the data model, the people editing it and the migrations that change it.

Django also owns sessions in the practical shared-schema split described in our migration guide. For an API on top, Django REST framework supports authentication policies, with packages for OAuth1a and OAuth2. Separate the question of staff login from the question of how external clients authenticate; they need not have the same interface.

FastAPI gives you security-scheme support for HTTP Basic, OAuth2 and API keys, plus dependencies that can handle authentication. That is not the same decision as obtaining an application’s user model, token storage and admin workflow. For example, FastAPI Users’ database-token strategy requires token models and a database adapter; account for that assembly work before calling the API-only route simpler.

The option most comparisons skip: run both

Run both when Django clearly owns the application and FastAPI clearly owns a separate external API, with Django handling admin, auth, ORM and migrations. In our combined stack, the frameworks are mounted as two ASGI apps in the same Python process, rather than deployed as two independent backends. Nginx exposes Django at /admin and FastAPI at /api, with both sharing the database connection.

For example, with an existing Django project named config, put the admin at the root of config/urls.py, then create gateway.py beside manage.py to mount Django at /admin and FastAPI at /api:

# config/urls.py
from django.contrib import admin
from django.urls import path

urlpatterns = [path("", admin.site.urls)]

# gateway.py
import os

os.environ.setdefault("DJANGO_SETTINGS_MODULE", "config.settings")

from django.core.asgi import get_asgi_application
from fastapi import FastAPI
from starlette.applications import Starlette
from starlette.routing import Mount

django_app = get_asgi_application()
api = FastAPI()

@api.get("/health")
def health():
    return {"ok": True}

app = Starlette(routes=[
    Mount("/admin", app=django_app),
    Mount("/api", app=api),
])

Install django, fastapi and uvicorn in the project environment. Run python manage.py migrate, then uvicorn gateway:app --reload. The example exposes the Django admin at /admin/ and the FastAPI health route at /api/health.

A shared PostgreSQL schema needs table ownership, not two tools making competing guesses. Our Django and FastAPI migration strategy recommends one owner per table: Django or Alembic, never both. Its practical split puts auth, sessions, admin and Django app tables under Django; event logs, API-specific entities and async job results can belong to Alembic.

Keep Django-managed tables out of Alembic’s target metadata, including django_migrations from Alembic’s reach. The deployment order in our guide is Django migrations first, Alembic second; it also recommends applying both histories to a clean database in CI to catch conflicts before deployment. These are ownership rules to enforce, not notes to leave in a diagram.

The cost is real: two migration histories, duplicate model definitions for shared tables and an ownership contract the team must maintain. I would not accept that cost for an early product merely to keep architectural options open; the migration guide itself suggests asking whether you need both frameworks, since Django alone or FastAPI with Alembic may be simpler. If both applications need the same settings, our shared pydantic-settings configuration guide covers feeding a validated settings object into Django’s settings.py.

Verdict: which to pick for your situation

Pick Django for an admin-heavy application; pick FastAPI for an API-first service. Choose both only after you can write down distinct route, data and migration ownership. Here is the decision matrix I would use before starting the repository.

Situation	Pick	Why
Content or admin-heavy CRUD app	Django	Put the data model and staff workflow first; add DRF if clients need an API.
API-first product or mobile backend	FastAPI	Start with typed request and response contracts, then make deliberate database and auth choices.
AI and LLM endpoints	FastAPI when the API orchestrates async calls	If the work outlasts a request, design the job and result contract separately.
Solo founder shipping an MVP	Django if the first useful release needs accounts and staff-managed records; FastAPI if the API itself is the product	Choose the framework that fits the first useful release without adding a second stack.
Team already on Django	Stay on Django for ordinary endpoints	A separate FastAPI surface needs a specific requirement, not a general speed argument.
Distinct internal application and external API	Consider both	Assign each table and route an owner before adopting the shared-schema design.

For LLM work, distinguish an async HTTP endpoint from a job that must finish after the response. Our FastAPI background-task and polling pattern for LLM jobs returns a job ID and has the client poll for status. The framework choice does not replace a decision about where that work runs.

Why choose FastAPI over Django? Choose it when typed API contracts, generated documentation and async route handling are the work you need the framework to do. If your main problem is administering records and accounts, that is an argument for Django, not a reason to assemble a second application around a shorter route function.

Frequently asked questions

Is Django outdated in 2026?

No: Django 6.0 added built-in interfaces for defining, validating, queuing and handling results for background tasks, although external workers still run them. Judge Django against the application you need, not against FastAPI’s API-first design.

Is FastAPI faster than Django?

FastAPI makes a strong performance claim for its framework, but that does not establish the latency of your application relative to Django. Benchmark the actual endpoint and its data access before choosing on speed.

Which is easier to learn, Django or FastAPI?

FastAPI uses standard Python type declarations, so its endpoint syntax does not require a new typing language. FastAPI leaves more surrounding choices for you to make.

Should I use Django REST Framework or FastAPI for an API?

Use DRF when the API naturally belongs to your Django models and application. Use FastAPI when typed request and response contracts, generated OpenAPI documentation or async routes are the stronger requirement.

Does FastAPI have an admin panel like Django?

The FastAPI stack described here does not provide Django’s admin as part of its API framework. If staff need that workflow, choose Django for it or explicitly budget for a separate solution.

Can Django and FastAPI be used together in one project?

Yes. Our combined architecture mounts them as ASGI apps in one process with separate routes and a shared database; give each database table one migration owner before you deploy it.

Sources

1. Django documentation | Django documentation | Django, docs.djangoproject.com
2. FastAPI - FastAPI, fastapi.tiangolo.com
3. Django 4.1 release notes — Django 6.2.dev20261026082354 documentation, django.readthedocs.io
4. Features - FastAPI, fastapi.tiangolo.com
5. Database - FastAPI Users, fastapi-users.github.io
6. Django REST framework, django-rest-framework.org
7. Home - FastAPI Tutorial, fastapi-tutorial.readthedocs.io
8. django/docs/releases/6.0.txt at main · django/django · GitHub, github.com