Django REST Framework has been one of the most popular choices for building APIs with Python for years.

It is mature, well documented, and deeply integrated with Django’s ORM, authentication, permissions, serializers, and admin ecosystem.

But then FastAPI arrived.

FastAPI quickly became popular for building modern APIs, particularly for microservices, asynchronous applications, AI systems, and high-performance backends.

This raises an increasingly common question:

Should I use FastAPI instead of Django REST Framework?

The answer is more nuanced than simply comparing benchmark numbers.

The real question is:

What kind of application are you building?

Let’s compare the two from an architectural perspective.

Django REST Framework vs FastAPI

At first glance, they solve a similar problem.

Both allow you to build APIs with Python.

But they come from very different philosophies.

Django REST Framework extends Django.

Django

Django
   │
   ├── ORM
   ├── Authentication
   ├── Admin
   ├── Middleware
   ├── Models
   └── Django REST Framework
             │
             └── API

FastAPI takes a more lightweight approach:

FastAPI
   │
   ├── Pydantic
   ├── Starlette
   ├── Dependency Injection
   └── Your database layer

FastAPI doesn’t try to provide an entire application ecosystem.

And that’s precisely one of its strengths.

1. Start With the Architecture
2. The biggest difference isn’t performance.
3. It’s architecture.
4. With Django REST Framework, you’re usually building inside a Django application.
5. For example:

class Order(models.Model):
    customer = models.ForeignKey(Customer, ...)
    amount = models.DecimalField(...)
    created_at = models.DateTimeField(...)

Then your API sits naturally on top:

class OrderViewSet(ModelViewSet):
    queryset = Order.objects.all()
    serializer_class = OrderSerializer

You get a lot for free.

FastAPI doesn’t impose an ORM or application architecture.

You can choose:

• SQLAlchemy
• SQLModel
• Tortoise ORM
• MongoDB
• PostgreSQL directly
• Another data access layer

That flexibility is powerful.

But it also means you have more architectural decisions to make.

2. Django REST Framework Wins When Django Is Already Your Platform

If you’re already using Django, DRF is often the obvious choice.

Imagine your application already has:

Users
Organizations
Permissions
Admin
Models
Billing
Notifications
Background jobs
Reports

Replacing DRF with FastAPI doesn’t automatically make this application better.

You would potentially need to reproduce or integrate many existing Django capabilities.

DRF gives you direct access to:

request.user

Django permissions:

permission_classes = [
    IsAuthenticated
]

And the ORM:

Order.objects.filter(
    customer=request.user
)

That’s a tremendous productivity advantage.

3. FastAPI Shines in Focused Services

Now imagine you’re building a service whose only responsibility is:

Receive event
      ↓
Process data
      ↓
Return result

For example:

• AI inference
• IoT gateway
• Hardware micro-agent
• Machine telemetry
• Image processing
• Real-time data processing
• Internal microservice

You may not need:

• Django Admin
• Django templates
• Django authentication
• Django’s entire application stack
• FastAPI becomes very attractive.

A service can be incredibly small:

from fastapi import FastAPI

app = FastAPI()

@app.get("/health")
async def health():
    return {"status": "ok"}

There is very little framework overhead.

4. Async Changes the Conversation

This is one of FastAPI’s strongest arguments.

FastAPI was designed with asynchronous Python applications in mind.

@app.get("/devices")
async def devices():
    result = await read_devices()
    return result

This is particularly useful for workloads involving a lot of I/O:

API
 │
 ├── External API
 ├── Database
 ├── Hardware
 ├── Message broker
 └── Another service

Instead of blocking while waiting for each operation, asynchronous code can efficiently manage concurrent I/O.

But there’s an important caveat.

Async doesn’t automatically make your application faster.

If your workload is primarily CPU-bound, simply adding async won’t solve the problem.

And Django has also evolved significantly in its support for asynchronous views and operations.

So the decision shouldn’t be based on the word “async” alone.

5. Performance Isn’t the Only Metric

FastAPI is frequently promoted through benchmarks.

And yes, FastAPI can deliver excellent performance.

But production API performance depends on much more than the framework.

Consider:

Framework
   ↓
Database queries
   ↓
Serialization
   ↓
External APIs
   ↓
Caching
   ↓
Network

An inefficient query can destroy the performance advantage of a lightweight framework.

This:

Order.objects.all()

followed by hundreds of unnecessary related-object queries can be far more damaging than the choice between DRF and FastAPI.

Good architecture beats framework benchmarks.

6. Validation: Both Are Excellent

FastAPI has a particularly elegant validation model.

Using Pydantic:

from pydantic import BaseModel

class OrderCreate(BaseModel):
    customer_id: int
    amount: float

FastAPI automatically validates incoming requests.

DRF has a similar concept with serializers:

class OrderSerializer(serializers.ModelSerializer):

    class Meta:
        model = Order
        fields = [
            "customer",
            "amount"
        ]

Both approaches work well.

The difference is philosophy.

FastAPI heavily embraces Python type hints.

DRF is deeply integrated with Django models and serializers.

7. Automatic API Documentation

FastAPI is particularly impressive here.

Define:

@app.post("/orders")
async def create_order(order: OrderCreate):
    ...

FastAPI automatically generates OpenAPI documentation.

You get interactive documentation with minimal configuration.

DRF also provides excellent OpenAPI tooling, but depending on your project and tooling choices, documentation can require more configuration.

For teams that value API contracts heavily, FastAPI’s approach is extremely appealing.

8. Authentication and Permissions

This is where Django starts to pull ahead.

Django has an extensive ecosystem around:

• Users
• Groups
• Permissions
• Sessions
• Authentication
• Admin
• OAuth integrations
• DRF builds directly on top of this.

For example:

class OrderViewSet(ModelViewSet):
    permission_classes = [
        IsAuthenticated
    ]

You can then implement more sophisticated authorization:

if request.user.role != "admin":
    ...

FastAPI has dependency injection, which is powerful:

async def get_current_user():
    ...

But you’re responsible for designing more of the authentication architecture.

This isn’t necessarily bad.

It simply means FastAPI gives you freedom instead of defaults.

9. The Admin Interface Is a Major Django Advantage

This is often underestimated.

Suppose your application contains:

Customers
Orders
Invoices
Companies
Payments
Tickets
Notifications

With Django, you can expose these through the admin interface relatively quickly.

@admin.register(Order)
class OrderAdmin(admin.ModelAdmin):
    list_display = (
        "id",
        "customer",
        "amount",
        "status"
    )

You immediately get an operational interface.

FastAPI doesn’t provide an equivalent built-in administration system.

If your business needs an internal back office, Django’s ecosystem can save enormous development time.

10. FastAPI Is Excellent for Microservices

This is where the comparison becomes particularly interesting.

Instead of replacing Django completely, you can use both.

For example:

                 Frontend
                    │
                    ▼
              Django / DRF
                    │
          ┌─────────┼──────────┐
          ▼         ▼          ▼
       FastAPI   FastAPI    FastAPI
        AI       IoT       Analytics

Django becomes the main business platform.

FastAPI handles specialized workloads.

This is often more practical than choosing one framework for everything.

11. A Hardware Example

Django handles:

• Users
• Organizations
• Business logic
• Permissions
• Database
• Reporting

FastAPI handles:

• Hardware communication
• Local device discovery
• Real-time commands
• Device events

This separation makes a lot of sense.

12. What About Analytics?

The same principle applies to analytics.

Your Django application might contain your transactional models:

Customer
Order
Payment
Invoice

But a dedicated FastAPI service could provide:

Analytics API
     │
     ├── Aggregations
     ├── Forecasting
     ├── Data processing
     └── External BI integration

The frontend doesn’t necessarily care which framework powers the endpoint.

It only cares about the API contract.

13. When Should You Choose DRF?

Choose Django REST Framework when:

Your application is already Django

Don’t introduce another framework without a reason.

You need a relational business application

Especially when you have complex relationships and workflows.

You need Django Admin

This can dramatically reduce development time.

You need mature authentication and permissions

Django provides an extensive ecosystem.

Your team knows Django

Developer productivity matters more than theoretical benchmarks.

14. When Should You Choose FastAPI?

FastAPI is a strong choice when:

You’re building a new API-only service

Especially when you don’t need Django’s broader ecosystem.

You have high I/O concurrency

For example:

API
 ↓
External services
 ↓
Message queues
 ↓
Hardware

You need a lightweight microservice

Small services benefit from minimal framework overhead.

You want strong type-driven APIs

Pydantic and Python type hints provide an excellent developer experience.

You’re building AI or data services

FastAPI has become particularly popular around ML inference and data-processing services.

15. Don’t Choose Based on Performance Alone

This is perhaps the most important lesson.

Don’t ask:

“Which framework is faster?”

Ask:

“Which framework makes this system easier to build, operate, and scale?”

A DRF application with:

Good indexes
Efficient queries
Caching
Pagination
Background jobs
Proper architecture

can outperform a poorly designed FastAPI application.

Likewise, a lightweight FastAPI service can be a much better choice for a focused high-concurrency workload.

16. The Hybrid Approach

For many organizations, the best answer isn’t:

Django or FastAPI.

It’s:

Django and FastAPI.

For example:

                 Web / Mobile
                      │
                      ▼
                Django REST API
                      │
        ┌─────────────┼─────────────┐
        │             │             │
        ▼             ▼             ▼
    PostgreSQL    FastAPI       FastAPI
                  Analytics     Hardware
                      │             │
                      ▼             ▼
                  ML / BI       Devices

Each technology does what it does best.

Django becomes the business platform.

FastAPI becomes the specialized service layer.

The Real Question Isn’t “Which Is Better?”

FastAPI isn’t the replacement for Django REST Framework.

And DRF isn’t necessarily the better choice simply because it is mature.

They optimize for different things.

| Requirement            |   DRF | FastAPI |
| ---------------------- | ----: | ------: |
| Django application     | ⭐⭐⭐⭐⭐ |      ⭐⭐ |
| Built-in ecosystem     | ⭐⭐⭐⭐⭐ |     ⭐⭐⭐ |
| Admin interface        | ⭐⭐⭐⭐⭐ |       — |
| Authentication         | ⭐⭐⭐⭐⭐ |     ⭐⭐⭐ |
| Type-driven APIs       |   ⭐⭐⭐ |   ⭐⭐⭐⭐⭐ |
| Async-first services   |   ⭐⭐⭐ |   ⭐⭐⭐⭐⭐ |
| Microservices          |  ⭐⭐⭐⭐ |   ⭐⭐⭐⭐⭐ |
| AI/ML APIs             |  ⭐⭐⭐⭐ |   ⭐⭐⭐⭐⭐ |
| Rapid CRUD development | ⭐⭐⭐⭐⭐ |    ⭐⭐⭐⭐ |
| Specialized services   |  ⭐⭐⭐⭐ |   ⭐⭐⭐⭐⭐ |

These aren’t absolute rankings — they’re architectural tendencies.

Final Thoughts

Choosing between Django REST Framework and FastAPI shouldn’t be a popularity contest.

DRF is excellent when your API is part of a larger Django application.

You get an ORM, authentication, permissions, administration, serializers, middleware, and a mature ecosystem.

FastAPI is excellent when your API is a focused service.

You get lightweight architecture, excellent type support, asynchronous capabilities, automatic OpenAPI documentation, and the freedom to choose the components around it.

And sometimes the best architecture uses both.

The interesting question isn’t:

“Should I replace DRF with FastAPI?”

It’s:

“Which part of my system actually needs FastAPI?”

That’s where the architectural decision becomes much more valuable than the framework debate.

FastAPI Instead of Django REST Framework: When Should You Make the Switch? was originally published in Django Unleashed on Medium, where people are continuing the conversation by highlighting and responding to this story.