Django vs FastAPI — when would you choose each, and what are the architectural trade-offs?

Comparison

Aspect	Django	FastAPI
Philosophy	Batteries included	Minimal, explicit
Async support	Partial (3.1+)	Native async/await
Performance	Moderate (~1K req/s)	Fast (~3-5K req/s)
Admin panel	Built-in, excellent	Manual or third-party
ORM	Django ORM (powerful)	SQLAlchemy (flexible)
API docs	Manual (drf-spectacular)	Auto-generated (Swagger)
Learning curve	Steep (conventions)	Easy (standard Python)
Type safety	Minimal	Full Pydantic validation
Ecosystem	Massive (packages)	Growing
Best for	Content sites, admin-heavy	APIs, microservices

Choose Django When:

• Need admin panel (manage users, content, data)
• Building content-heavy sites (CMS, e-commerce)
• Team already knows Django well
• Need ORM migrations + Django ecosystem

Choose FastAPI When:

• Building pure API / microservice
• Need high performance and async
• Want auto-generated API docs
• Type validation is critical
• Building real-time features (WebSocket)

Hybrid Approach (Common)

Django (monolith):
  - Admin panel, user management, content
  - /admin/ → Django admin
  - /api/v2/ → Django REST Framework

FastAPI (microservice):
  - High-performance API endpoints
  - Real-time features
  - ML model serving

FastAPI Example (type-safe API)

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Application(BaseModel):
    company: str
    position: str
    salary: float | None = None

@app.post("/applications")
async def create_application(app_data: Application):
    # Pydantic validates request body automatically
    return await db.create(app_data)

# Auto-generated Swagger docs at /docs