Does Django Work With Vercel?

Partially CompatibleLast verified: 2026-02-20

Django can run on Vercel, but only via serverless functions—Vercel is optimized for static/frontend deployment, not traditional Django applications.

Quick Facts

Compatibility
partial
Setup Difficulty
Complex
Official Integration
No — community maintained
Confidence
high
Minimum Versions
Django: 3.1

How Django Works With Vercel

Django and Vercel have a misaligned architecture. Vercel is built for frontend frameworks (Next.js, React) and static content with edge caching. Django is a traditional server framework expecting persistent connections and stateful sessions. You can deploy Django to Vercel using serverless functions (Python runtime), but this requires restructuring your app as a collection of handler functions rather than a typical Django project. Each request triggers a cold start, making performance unpredictable. Database connections in serverless are problematic because Django's ORM expects persistent connections. You'll need connection pooling (like PgBouncer) and must handle stateless request processing carefully. The real use case is treating Vercel as an API backend with a separate frontend deployment, or running Django on traditional infrastructure (Railway, Heroku, AWS) while using Vercel exclusively for your frontend. For most Django projects, serverless deployment via AWS Lambda, Google Cloud Functions, or Railway is more mature and practical.

Best Use Cases

Decoupled architecture: Django REST API backend on traditional hosting with a Next.js/React frontend on Vercel
Lightweight Python APIs: Small, stateless Django endpoints consumed by a Vercel-deployed frontend application
Hobby projects: Low-traffic Django apps using Vercel's free tier with PostgreSQL connection pooling
Microservices: Individual Django endpoints as part of a larger edge-compute strategy with Vercel middleware

Django on Vercel Serverless Handler

bash
pip install django python-dotenv
python
# api/handler.py
import os
import sys
import django
from django.conf import settings
from django.http import JsonResponse

# Configure Django
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'config.settings')
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
django.setup()

from django.core.wsgi import get_wsgi_application

wsgi_app = get_wsgi_application()

def handler(request):
    """Vercel serverless function handler"""
    # Convert Vercel request to WSGI environ
    environ = {
        'REQUEST_METHOD': request['httpMethod'],
        'PATH_INFO': request['path'],
        'QUERY_STRING': request.get('queryStringParameters', ''),
        'SERVER_NAME': 'vercel',
        'SERVER_PORT': '443',
        'wsgi.url_scheme': 'https',
    }
    
    # Call Django WSGI app
    return wsgi_app(environ, lambda *args: None)

Known Issues & Gotchas

critical

Cold starts cause 10-30s latency on first request, unacceptable for real-time applications

Fix: Use Vercel for frontend only; host Django separately on Railway, Render, or AWS for backend

critical

Django's persistent database connections fail in serverless; connection pooling required

Fix: Implement PgBouncer or use managed connection pooling; recycle connections per request

warning

Session state lost between requests; in-memory caches (Redis) required

Fix: Configure Django to use Redis or external session backend instead of default database sessions

warning

File uploads to /tmp are ephemeral and lost after function execution

Fix: Stream uploads directly to S3/cloud storage; never rely on local filesystem

Alternatives

  • Next.js API routes + Django/FastAPI backend on Railway or Render (better separation of concerns)
  • FastAPI + Vercel Functions (Python async framework better suited for serverless cold starts)
  • Django + AWS Lambda + API Gateway (more mature serverless Django ecosystem with better tooling)

Resources

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