RESTful API vs FastAPI: A Developer's Comparison

APIs are essential to modern software development, and choosing the right approach can impact everything from development speed to system performance. Two common paths in the Python ecosystem are RESTful API design and using FastAPI, a modern web framework.

In this post, we'll explore what each one means, how they differ, and when to use each.

What is a RESTful API?

A RESTful API is an API that follows the architectural principles of REST (Representational State Transfer). It's not a specific tool or library, but a way of designing web services to be stateless, resource-based, and rely on standard HTTP methods.

Core REST Principles:

• Statelessness

• Use of standard HTTP verbs: GET, POST, PUT, DELETE

• URL endpoints represent resources (e.g., /users/123)

• Client-server separation

• Support for multiple formats like JSON and XML

Example (Conceptual REST):

You can implement RESTful APIs using frameworks like Flask, Django REST Framework, or Express.js (for JavaScript).

What is FastAPI?

FastAPI is a modern, fast (high-performance) web framework for building APIs with Python 3.7+ based on standard Python type hints. It is designed to be easy to use, highly performant, and developer-friendly.

Why FastAPI stands out:

• Built on Starlette (web toolkit) and Pydantic (data validation)

• Native support for asynchronous programming (async/await)

• Auto-generates OpenAPI docs and Swagger UI

• Validates request/response data using Python types

• Offers fast JSON serialization and minimal overhead

Example (FastAPI code):

When you visit /docs, FastAPI gives you interactive API documentation automatically.

RESTful API vs FastAPI Comparison

1. Type:

• RESTful API is an architectural style that defines a set of constraints for creating web services.

• FastAPI is a Python web framework specifically designed for building APIs.

2. Language Specificity:

• RESTful API is language-agnostic — it can be implemented in any programming language.

• FastAPI is Python-only and tightly integrated with Python features.

3. Performance:

• RESTful API performance depends on the specific implementation and technology stack.

• FastAPI offers very high performance due to its use of asynchronous programming and Starlette under the hood.

4. Data Validation:

• RESTful API usually requires manual data validation or integration with external libraries.

• FastAPI uses Pydantic for automatic data validation and serialization.

5. API Documentation:

• RESTful API often needs manual documentation or separate tools like Swagger/OpenAPI generators.

• FastAPI provides auto-generated interactive documentation using Swagger UI and ReDoc by default.

6. Learning Curve:

• RESTful API has a low to medium learning curve, depending on how it's implemented.

• FastAPI has a moderate learning curve, especially due to the use of Python type hints and async features.

7. Best Use Case:

• RESTful API is ideal for any backend architecture, regardless of language.

• FastAPI is best suited for modern APIs developed in Python, especially when speed and automatic documentation are priorities.

When Should You Use Each?

Use RESTful API (Design) if:

• You're working in a multi-language ecosystem.

• You need a design-agnostic structure.

• You're following existing company architecture guidelines.

Use FastAPI if:

• You're working with Python and want to move fast.

• You need high performance and async support.

• You want automatic docs and built-in validation.

Conclusion

While RESTful APIs and FastAPI are often compared, they serve different purposes. RESTful API is a design paradigm, whereas FastAPI is a concrete implementation built for speed and developer efficiency.

If you're using Python and want a clean, performant, and scalable way to build APIs, FastAPI is one of the best choices available today. If you're designing APIs at a higher level or across multiple platforms, RESTful architecture provides a solid foundation.

Let your use case-and your stack-guide your decision.