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Django REST Framework vs Django Ninja: A Comprehensive Comparison for API Development

Posted on September 1, 2025
KFSys

By KFSys

System Administrator

When building APIs with Django, developers typically face a choice between two powerful frameworks: Django REST Framework (DRF) and Django Ninja. Both serve the same fundamental purpose—creating robust REST APIs—but take dramatically different approaches to achieve this goal.

This tutorial provides an in-depth technical comparison to help you choose the right tool for your project.

Quick Overview

Django REST Framework (DRF)

  • Mature, battle-tested framework (2011)
  • Django-native approach with class-based views
  • Extensive ecosystem and third-party packages
  • Powerful serialization and validation system
  • Built-in authentication, permissions, and pagination

Django Ninja

  • Modern framework inspired by FastAPI (2021)
  • Type hints and automatic documentation
  • Performance-focused with async support
  • Lightweight and intuitive API design
  • Built-in OpenAPI/Swagger documentation


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Architecture and Philosophy

Django REST Framework: The Django Way

DRF follows Django’s philosophy closely, extending Django’s patterns into the API realm:

# DRF ViewSet approach
from rest_framework import viewsets, serializers
from rest_framework.response import Response
from .models import Book

class BookSerializer(serializers.ModelSerializer):
    class Meta:
        model = Book
        fields = '__all__'

class BookViewSet(viewsets.ModelViewSet):
    queryset = Book.objects.all()
    serializer_class = BookSerializer

    def create(self, request):
        serializer = self.get_serializer(data=request.data)
        serializer.is_valid(raise_exception=True)
        book = serializer.save()
        return Response(serializer.data, status=201)

Django Ninja: The FastAPI-Inspired Approach

Ninja embraces modern Python features and prioritizes developer experience:

# Django Ninja approach
from ninja import NinjaAPI, Schema
from typing import List
from .models import Book

api = NinjaAPI()

class BookSchema(Schema):
    title: str
    author: str
    isbn: str
    published_date: date

class BookOut(Schema):
    id: int
    title: str
    author: str
    isbn: str

@api.post("/books", response=BookOut)
def create_book(request, book: BookSchema):
    book_instance = Book.objects.create(**book.dict())
    return book_instance

Performance Comparison

Benchmarks and Overhead

Django Ninja generally outperforms DRF in raw throughput:

# Performance test setup
import time
from django.test import TestCase, Client

class PerformanceTest(TestCase):
    def setUp(self):
        self.client = Client()
        # Create test data
        for i in range(1000):
            Book.objects.create(
                title=f"Book {i}",
                author=f"Author {i}",
                isbn=f"978-{i:010d}"
            )

    def test_list_performance(self):
        # DRF endpoint
        start = time.time()
        response = self.client.get('/api/drf/books/')
        drf_time = time.time() - start

        # Ninja endpoint
        start = time.time()
        response = self.client.get('/api/ninja/books/')
        ninja_time = time.time() - start

        print(f"DRF: {drf_time:.4f}s, Ninja: {ninja_time:.4f}s")

Typical Results:

  • Django Ninja: ~20-30% faster for simple CRUD operations
  • DRF: Comparable performance with heavy serialization logic
  • Async operations: Ninja has significant advantages

Memory Usage

# Memory profiling example
import tracemalloc

tracemalloc.start()

# Your API calls here
response = client.get('/api/books/')

current, peak = tracemalloc.get_traced_memory()
print(f"Current memory usage: {current / 1024 / 1024:.2f} MB")
print(f"Peak memory usage: {peak / 1024 / 1024:.2f} MB")

Type Safety and Validation

DRF Serializers vs Ninja Schemas

DRF Validation:

class BookSerializer(serializers.ModelSerializer):
    title = serializers.CharField(max_length=200)
    isbn = serializers.CharField(validators=[isbn_validator])

    class Meta:
        model = Book
        fields = ['title', 'author', 'isbn', 'published_date']

    def validate_isbn(self, value):
        if not value.startswith('978'):
            raise serializers.ValidationError("ISBN must start with 978")
        return value

    def validate(self, data):
        if data['published_date'] > timezone.now().date():
            raise serializers.ValidationError("Publication date cannot be in the future")
        return data

Ninja Schema Validation:

from pydantic import validator
from datetime import date

class BookSchema(Schema):
    title: str = Field(..., max_length=200)
    author: str
    isbn: str
    published_date: date

    @validator('isbn')
    def validate_isbn(cls, v):
        if not v.startswith('978'):
            raise ValueError('ISBN must start with 978')
        return v

    @validator('published_date')
    def validate_publication_date(cls, v):
        if v > date.today():
            raise ValueError('Publication date cannot be in the future')
        return v

Authentication and Permissions

DRF Authentication System

from rest_framework.authentication import TokenAuthentication
from rest_framework.permissions import IsAuthenticated
from rest_framework.decorators import action

class BookViewSet(viewsets.ModelViewSet):
    authentication_classes = [TokenAuthentication]
    permission_classes = [IsAuthenticated]

    @action(detail=True, methods=['post'])
    def set_favorite(self, request, pk=None):
        book = self.get_object()
        # Custom logic here
        return Response({'status': 'favorite set'})

Ninja Authentication

from ninja.security import HttpBearer
from django.contrib.auth import authenticate

class AuthBearer(HttpBearer):
    def authenticate(self, request, token):
        try:
            user = Token.objects.get(key=token).user
            return user
        except Token.DoesNotExist:
            return None

@api.post("/books", auth=AuthBearer())
def create_book(request, book: BookSchema):
    # request.auth contains the authenticated user
    return Book.objects.create(**book.dict())

Advanced Features Comparison

Filtering and Searching

DRF with django-filter:

from django_filters.rest_framework import DjangoFilterBackend
from rest_framework.filters import SearchFilter

class BookViewSet(viewsets.ModelViewSet):
    filter_backends = [DjangoFilterBackend, SearchFilter]
    filterset_fields = ['author', 'published_date']
    search_fields = ['title', 'author']

    def get_queryset(self):
        queryset = Book.objects.all()
        author = self.request.query_params.get('author')
        if author:
            queryset = queryset.filter(author__icontains=author)
        return queryset

Ninja Filtering:

from ninja import Query

@api.get("/books")
def list_books(request,
               author: str = Query(None),
               search: str = Query(None),
               limit: int = Query(10)):
    books = Book.objects.all()

    if author:
        books = books.filter(author__icontains=author)
    if search:
        books = books.filter(title__icontains=search)

    return books[:limit]

Pagination

DRF Pagination:

from rest_framework.pagination import PageNumberPagination

class BookPagination(PageNumberPagination):
    page_size = 20
    page_size_query_param = 'page_size'
    max_page_size = 100

class BookViewSet(viewsets.ModelViewSet):
    pagination_class = BookPagination

Ninja Pagination:

@api.get("/books")
def list_books(request,
               page: int = Query(1),
               page_size: int = Query(20)):
    offset = (page - 1) * page_size
    books = Book.objects.all()[offset:offset + page_size]
    total = Book.objects.count()

    return {
        "items": books,
        "total": total,
        "page": page,
        "pages": (total + page_size - 1) // page_size
    }

Testing Strategies

DRF Testing

from rest_framework.test import APITestCase
from rest_framework import status

class BookAPITest(APITestCase):
    def setUp(self):
        self.user = User.objects.create_user('testuser', 'test@test.com', 'pass')
        self.client.force_authenticate(user=self.user)

    def test_create_book(self):
        data = {
            'title': 'Test Book',
            'author': 'Test Author',
            'isbn': '9781234567890'
        }
        response = self.client.post('/api/books/', data)
        self.assertEqual(response.status_code, status.HTTP_201_CREATED)
        self.assertEqual(Book.objects.count(), 1)

Ninja Testing

from django.test import TestCase, Client

class BookNinjaTest(TestCase):
    def setUp(self):
        self.client = Client()
        self.user = User.objects.create_user('testuser', 'test@test.com', 'pass')

    def test_create_book(self):
        self.client.force_login(self.user)
        data = {
            'title': 'Test Book',
            'author': 'Test Author',
            'isbn': '9781234567890'
        }
        response = self.client.post('/api/books/',
                                  data=json.dumps(data),
                                  content_type='application/json')
        self.assertEqual(response.status_code, 201)

Community and Ecosystem

Django REST Framework

  • GitHub Stars: ~27k stars, very active community
  • Third-party Packages: Extensive ecosystem
    • django-oauth-toolkit for OAuth2
    • django-rest-swagger for documentation
    • django-filter for advanced filtering
    • drf-spectacular for OpenAPI 3.0
  • Learning Resources: Extensive documentation, tutorials, courses
  • Enterprise Adoption: Widely used in production

Django Ninja

  • GitHub Stars: ~5k stars, growing rapidly
  • Third-party Packages: Smaller but growing ecosystem
  • Learning Resources: Good documentation, fewer tutorials
  • Enterprise Adoption: Newer, but gaining traction

Use Cases and Decision Matrix

Choose Django REST Framework When:

  1. Legacy Integration: Working with existing Django projects
  2. Complex Permissions: Need sophisticated permission systems
  3. Team Familiarity: Team already knows DRF patterns
  4. Enterprise Requirements: Need proven, stable solution
  5. Rich Ecosystem: Require specific third-party integrations
# Example: Complex enterprise API with custom permissions
class AuthorPermission(BasePermission):
    def has_object_permission(self, request, view, obj):
        if request.method in SAFE_METHODS:
            return True
        return obj.author == request.user

class BookViewSet(viewsets.ModelViewSet):
    permission_classes = [AuthorPermission]
    filter_backends = [DjangoFilterBackend, SearchFilter, OrderingFilter]
    filterset_class = BookFilter
    search_fields = ['title', 'author', 'description']
    ordering_fields = ['created_at', 'title']

Choose Django Ninja When:

  1. New Projects: Starting fresh with modern Python
  2. Type Safety: Want compile-time type checking
  3. Performance: Need maximum API performance
  4. Developer Experience: Prefer intuitive, modern syntax
  5. Auto Documentation: Want built-in OpenAPI docs
# Example: Modern API with type safety
from typing import Optional
from ninja import NinjaAPI, Schema
from ninja.pagination import paginate

api = NinjaAPI(title="Book API", version="1.0.0")

@api.get("/books", response=List[BookOut])
@paginate
def list_books(request,
               author: Optional[str] = None,
               genre: Optional[str] = None):
    books = Book.objects.all()
    if author:
        books = books.filter(author__icontains=author)
    if genre:
        books = books.filter(genre=genre)
    return books

Migration Strategies

From DRF to Ninja

# Step 1: Gradual migration approach
# Keep existing DRF endpoints, add new ones with Ninja

# urls.py
urlpatterns = [
    path('api/v1/', include('myapp.drf_urls')),  # Existing DRF
    path('api/v2/', api.urls),                   # New Ninja API
]

# Step 2: Convert serializers to schemas
# DRF Serializer
class BookSerializer(serializers.ModelSerializer):
    class Meta:
        model = Book
        fields = '__all__'

# Equivalent Ninja Schema
class BookSchema(ModelSchema):
    class Config:
        model = Book
        model_fields = '__all__'

Best Practices

DRF Best Practices

# 1. Use ViewSets for consistent CRUD operations
class BookViewSet(viewsets.ModelViewSet):
    queryset = Book.objects.select_related('author')
    serializer_class = BookSerializer

    def get_queryset(self):
        # Always optimize queries
        return super().get_queryset().select_related('author')

# 2. Custom serializer methods for complex logic
class BookSerializer(serializers.ModelSerializer):
    author_name = serializers.SerializerMethodField()

    def get_author_name(self, obj):
        return f"{obj.author.first_name} {obj.author.last_name}"

# 3. Use serializer validation
def validate_isbn(self, value):
    if Book.objects.filter(isbn=value).exists():
        raise serializers.ValidationError("ISBN already exists")
    return value

Ninja Best Practices

# 1. Use dependency injection for reusable logic
def get_current_user(request):
    return request.user if request.user.is_authenticated else None

@api.get("/books")
def list_books(request, user=Depends(get_current_user)):
    if user:
        return Book.objects.filter(owner=user)
    return Book.objects.filter(is_public=True)

# 2. Use response models for consistent output
class BookResponse(Schema):
    id: int
    title: str
    author: str
    created_at: datetime

@api.get("/books/{book_id}", response=BookResponse)
def get_book(request, book_id: int):
    return get_object_or_404(Book, id=book_id)

# 3. Handle errors gracefully
@api.exception_handler(ValidationError)
def validation_errors(request, exc):
    return api.create_response(
        request,
        {"errors": exc.errors()},
        status=422
    )

Performance Optimization Tips

Database Optimization (Both Frameworks)

# Use select_related for foreign keys
books = Book.objects.select_related('author', 'publisher')

# Use prefetch_related for many-to-many
books = Book.objects.prefetch_related('genres', 'reviews')

# Implement database indexing
class Book(models.Model):
    title = models.CharField(max_length=200, db_index=True)
    isbn = models.CharField(max_length=13, unique=True)

    class Meta:
        indexes = [
            models.Index(fields=['author', 'published_date']),
            models.Index(fields=['title', 'author']),
        ]

Caching Strategies

# DRF with cache
from django.core.cache import cache

class BookViewSet(viewsets.ModelViewSet):
    def list(self, request):
        cache_key = f"books_list_{hash(str(request.GET))}"
        cached_result = cache.get(cache_key)
        if cached_result:
            return Response(cached_result)

        response = super().list(request)
        cache.set(cache_key, response.data, timeout=300)
        return response

# Ninja with cache
@api.get("/books")
def list_books(request):
    cache_key = "books_list"
    cached_books = cache.get(cache_key)
    if cached_books:
        return cached_books

    books = list(Book.objects.all())
    cache.set(cache_key, books, timeout=300)
    return books

Conclusion

Both Django REST Framework and Django Ninja are excellent choices for building APIs, but they serve different needs:

Choose DRF if you:

  • Need maximum stability and community support
  • Are working with complex, existing Django applications
  • Require extensive third-party integrations
  • Have a team already familiar with Django patterns

Choose Ninja if you:

  • Want modern Python development with type hints
  • Need maximum performance and minimal overhead
  • Prefer intuitive, FastAPI-like syntax
  • Are building new APIs from scratch

The decision ultimately depends on your project requirements, team expertise, and long-term maintenance considerations. Both frameworks will continue to evolve, with Ninja likely gaining more adoption as teams embrace modern Python practices.

For new projects where performance and developer experience are priorities, Django Ninja offers compelling advantages. For established applications or teams requiring battle-tested stability, Django REST Framework remains the safer choice.

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