Building APIs with FastAPI vs Django: A Comprehensive Comparison

When building APIs with Python, two frameworks stand out as popular choices: FastAPI and Django (specifically Django REST Framework). Both are powerful, well-documented, and have strong community support, but they serve different needs and have distinct philosophies. This comprehensive comparison will help you choose the right framework for your next API project.

Table of Contents

Overview

FastAPI

FastAPI is a modern, high-performance web framework designed specifically for building APIs. Created by Sebastián Ramirez in 2018, it leverages Python type hints and is built on Starlette and Pydantic, making it incredibly fast and developer-friendly.

Django + Django REST Framework

Django is a mature, “batteries-included” web framework that has been around since 2005. When combined with Django REST Framework (DRF), it becomes a powerful tool for building robust APIs with extensive built-in features.

Performance Comparison

FastAPI Performance

# FastAPI example - High performance
from fastapi import FastAPI
import asyncio

app = FastAPI()

@app.get("/async-data")
async def get_async_data():
    # Native async support
    await asyncio.sleep(0.1)
    return {"message": "Fast async response"}

@app.get("/users/{user_id}")
async def get_user(user_id: int):
    return {"user_id": user_id, "name": "John Doe"}

Performance Characteristics:

• Speed: One of the fastest Python frameworks available
• Async Native: Built-in async/await support
• Benchmarks: Often 2-3x faster than Django in API-only scenarios
• Concurrency: Excellent handling of concurrent requests

Django Performance

# Django REST Framework example
from rest_framework.decorators import api_view
from rest_framework.response import Response
from django.contrib.auth.models import User

@api_view(['GET'])
def get_user(request, user_id):
    try:
        user = User.objects.get(id=user_id)
        return Response({
            'user_id': user.id,
            'name': user.get_full_name()
        })
    except User.DoesNotExist:
        return Response({'error': 'User not found'}, status=404)

Performance Characteristics:

• Speed: Good performance, optimized over years
• Async: Limited async support (improving in recent versions)
• Benchmarks: Solid but not as fast as FastAPI for pure API workloads
• Concurrency: Traditional WSGI model, though ASGI support is growing

Development Experience

FastAPI Developer Experience

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import List, Optional

app = FastAPI(title="User API", version="1.0.0")

class User(BaseModel):
    id: int
    name: str
    email: str
    age: Optional[int] = None

class UserCreate(BaseModel):
    name: str
    email: str
    age: Optional[int] = None

@app.post("/users/", response_model=User)
async def create_user(user: UserCreate):
    # Automatic validation through Pydantic
    new_user = User(id=1, **user.dict())
    return new_user

@app.get("/users/", response_model=List[User])
async def list_users():
    return [
        User(id=1, name="John Doe", email="john@example.com", age=30)
    ]

Advantages:

• Type Safety: Built-in type hints and validation
• Auto Documentation: Automatic OpenAPI/Swagger docs
• Modern Python: Leverages latest Python features
• Minimal Boilerplate: Clean, concise code
• IDE Support: Excellent autocomplete and error detection

Django Developer Experience

# models.py
from django.db import models
from django.contrib.auth.models import AbstractUser

class User(models.Model):
    name = models.CharField(max_length=100)
    email = models.EmailField(unique=True)
    age = models.IntegerField(null=True, blank=True)
    created_at = models.DateTimeField(auto_now_add=True)

# serializers.py
from rest_framework import serializers

class UserSerializer(serializers.ModelSerializer):
    class Meta:
        model = User
        fields = ['id', 'name', 'email', 'age', 'created_at']

# views.py
from rest_framework.viewsets import ModelViewSet

class UserViewSet(ModelViewSet):
    queryset = User.objects.all()
    serializer_class = UserSerializer

Advantages:

• Batteries Included: Extensive built-in features
• ORM: Powerful database abstraction layer
• Admin Interface: Automatic admin panel
• Mature Ecosystem: Thousands of third-party packages
• Convention: Well-established patterns and practices

Feature Comparison

Real-World Examples

FastAPI: Microservice Architecture

from fastapi import FastAPI, Depends, HTTPException
from sqlalchemy.orm import Session
import databases
import sqlalchemy

# Database setup
DATABASE_URL = "postgresql://user:password@localhost/dbname"
database = databases.Database(DATABASE_URL)

app = FastAPI()

@app.on_event("startup")
async def startup():
    await database.connect()

@app.on_event("shutdown")
async def shutdown():
    await database.disconnect()

# Lightweight service for user authentication
@app.post("/auth/login")
async def login(credentials: LoginCredentials):
    # Fast authentication logic
    token = await authenticate_user(credentials)
    return {"access_token": token, "token_type": "bearer"}

# High-performance data endpoint
@app.get("/analytics/users")
async def get_user_analytics():
    query = "SELECT COUNT(*) as total_users FROM users"
    result = await database.fetch_one(query)
    return {"total_users": result["total_users"]}

Django: Full-Featured Application

# models.py
from django.db import models
from django.contrib.auth.models import AbstractUser

class CustomUser(AbstractUser):
    profile_image = models.ImageField(upload_to='profiles/')
    bio = models.TextField(max_length=500, blank=True)
    birth_date = models.DateField(null=True, blank=True)

class Post(models.Model):
    author = models.ForeignKey(CustomUser, on_delete=models.CASCADE)
    title = models.CharField(max_length=200)
    content = models.TextField()
    created_at = models.DateTimeField(auto_now_add=True)
    tags = models.ManyToManyField('Tag', blank=True)

class Tag(models.Model):
    name = models.CharField(max_length=50, unique=True)

# admin.py
from django.contrib import admin

@admin.register(Post)
class PostAdmin(admin.ModelAdmin):
    list_display = ['title', 'author', 'created_at']
    list_filter = ['created_at', 'tags']
    search_fields = ['title', 'content']

# Complex business logic with built-in features
class PostViewSet(ModelViewSet):
    queryset = Post.objects.all()
    serializer_class = PostSerializer
    permission_classes = [IsAuthenticatedOrReadOnly]
    filter_backends = [DjangoFilterBackend, SearchFilter]
    filterset_fields = ['author', 'tags']
    search_fields = ['title', 'content']

When to Choose FastAPI

Ideal Use Cases:

• API-First Applications: Building microservices or API-only backends
• High Performance Requirements: Applications needing maximum speed
• Modern Python Development: Teams wanting to use latest Python features
• Documentation-Heavy Projects: APIs requiring excellent documentation
• Real-time Applications: WebSocket and async-heavy applications

Example Scenarios:

# IoT data collection service
@app.post("/sensor-data")
async def collect_sensor_data(data: List[SensorReading]):
    # High-throughput data ingestion
    await process_sensor_data_async(data)
    return {"status": "processed", "count": len(data)}

# Machine learning model serving
@app.post("/predict")
async def predict(features: MLFeatures):
    prediction = await model.predict_async(features.dict())
    return {"prediction": prediction, "confidence": 0.95}

When to Choose Django

Ideal Use Cases:

• Full-Stack Applications: When you need both API and web interface
• Rapid Development: Prototyping and MVP development
• Content Management: Applications with admin requirements
• Enterprise Applications: Large, complex systems with many features
• Team Familiarity: Teams already experienced with Django

Example Scenarios:

# E-commerce platform
class Product(models.Model):
    name = models.CharField(max_length=200)
    price = models.DecimalField(max_digits=10, decimal_places=2)
    inventory = models.IntegerField()

    def apply_discount(self, percentage):
        # Complex business logic
        return self.price * (1 - percentage / 100)

# Content management system
class Article(models.Model):
    title = models.CharField(max_length=200)
    content = models.TextField()
    author = models.ForeignKey(User, on_delete=models.CASCADE)
    published = models.BooleanField(default=False)

    class Meta:
        permissions = [
            ("can_publish", "Can publish articles"),
        ]

Migration Considerations

From Django to FastAPI

# Gradual migration approach
# Keep Django for admin and complex business logic
# Add FastAPI for new high-performance endpoints

# FastAPI service
from fastapi import FastAPI
from django.core.wsgi import get_wsgi_application
from fastapi.middleware.wsgi import WSGIMiddleware

fastapi_app = FastAPI()

@fastapi_app.get("/api/v2/fast-endpoint")
async def new_fast_endpoint():
    return {"message": "New FastAPI endpoint"}

# Mount Django app for existing functionality
django_app = get_wsgi_application()
fastapi_app.mount("/admin", WSGIMiddleware(django_app))

From FastAPI to Django

# When you need more built-in features
# Gradual migration: Add Django ORM while keeping FastAPI routes

from django.conf import settings
import django
from django.apps import apps

# Configure Django ORM in FastAPI
settings.configure(
    DATABASES={
        'default': {
            'ENGINE': 'django.db.backends.postgresql',
            'NAME': 'your_db',
        }
    },
    INSTALLED_APPS=['your_app'],
)
django.setup()

# Use Django models in FastAPI
from your_app.models import User as DjangoUser

@app.get("/users/{user_id}")
async def get_user(user_id: int):
    user = await sync_to_async(DjangoUser.objects.get)(id=user_id)
    return {"id": user.id, "name": user.name}

Performance Benchmarks

Simple API Endpoint Comparison

# FastAPI (requests/second)
GET /users/1: ~15,000 req/s

# Django + DRF (requests/second)
GET /users/1: ~5,000 req/s

# With database queries
FastAPI + SQLAlchemy: ~8,000 req/s
Django + ORM: ~4,000 req/s

Async Operations

# FastAPI excels in async scenarios
@app.get("/concurrent-operations")
async def concurrent_ops():
    tasks = [
        fetch_user_data(user_id) for user_id in range(100)
    ]
    results = await asyncio.gather(*tasks)
    return {"processed": len(results)}

# Django async support (Django 4.1+)
from django.http import JsonResponse
from asgiref.sync import sync_to_async

async def async_view(request):
    users = await sync_to_async(list)(User.objects.all())
    return JsonResponse({"count": len(users)})

Decision Matrix

Conclusion

Choose FastAPI when:

• Building API-only applications or microservices
• Performance is a top priority
• You want modern Python development with type hints
• Your team values automatic documentation
• You’re building real-time or async-heavy applications

Choose Django + DRF when:

• Building full-stack applications with web interfaces
• You need rapid development with many built-in features
• Your application requires complex business logic and admin interfaces
• You’re working with a team familiar with Django
• You need a mature, battle-tested framework for enterprise applications

Both frameworks are excellent choices, and the decision often comes down to your specific requirements, team expertise, and project constraints. Many successful projects use a hybrid approach, leveraging Django’s admin and ORM capabilities alongside FastAPI’s performance for critical API endpoints.

The Python ecosystem is rich enough to support both approaches, and you can’t go wrong with either choice when applied to the right use case.