APIs (Application Programming Interfaces) are the backbone of modern software development. Whether you’re building a mobile app, a single-page web app, or a complex microservices architecture, APIs enable seamless communication between systems. As technology evolves, developers are often faced with a critical decision: Should you use REST or GraphQL? Both are widely adopted and serve the same fundamental purpose, but each has its own strengths, limitations, and ideal use cases.
In this article, we’ll explore what REST and GraphQL are, how they differ, and when you should use one over the other in modern software development.
What Is REST?
REST (Representational State Transfer) is an architectural style for designing networked applications. It uses standard HTTP methods such as GET, POST, PUT, and DELETE, and it structures data in the form of resources, usually accessible via URL endpoints.
For example, to fetch a user’s data, you’d hit a URL like:
bashCopyEditGET /users/123
REST APIs often return data in JSON format and are known for their simplicity and widespread support.
Key Features of REST:
- Resource-based structure (e.g.,
/users,/posts) - Stateless interactions
- Cacheable responses
- Utilizes HTTP verbs and status codes
What Is GraphQL?
GraphQL, developed by Facebook in 2012 and open-sourced in 2015, is a query language for your API as well as a runtime for executing those queries. Unlike REST, where you hit specific endpoints for different resources, GraphQL provides a single endpoint and lets the client decide what data it needs.
Here’s an example query:
graphqlCopyEdit{
user(id: "123") {
name
email
posts {
title
comments {
text
}
}
}
}
With one request, you can fetch deeply nested and specific fields.
Key Features of GraphQL:
- Single endpoint for all operations
- Fetch exactly what you need, no more, no less
- Strongly typed schema
- Real-time support via subscriptions
REST vs. GraphQL: Key Differences
| Feature | REST | GraphQL |
|---|---|---|
| Endpoints | Multiple endpoints | Single endpoint |
| Data Fetching | Fixed structure per endpoint | Custom queries allow flexible fetching |
| Over-fetching | Common, returns unnecessary data | Avoided by fetching specific fields |
| Under-fetching | Requires multiple calls for nested data | Single query can fetch all needed data |
| Caching | Easier via HTTP caching | Complex, but possible with custom logic |
| Versioning | Often requires new versions (v1, v2) | Avoided via schema evolution |
| Learning Curve | Lower | Steeper due to schema and query language |
| Tooling | Mature, widely supported | Growing rapidly, especially with Apollo |
When to Use REST
REST is still a strong choice for many applications, especially when:
- You need to build a simple CRUD API.
- Caching is critical (e.g., public APIs).
- You’re working with legacy systems or third-party APIs.
- Your development team is more familiar with RESTful patterns.
It’s widely supported by tools, documentation, and frameworks in all major programming languages.
When to Use GraphQL
GraphQL shines in more complex, data-intensive applications, particularly when:
- You need highly flexible client requests (e.g., mobile apps or SPAs).
- Your API requires aggregated data from multiple sources.
- The frontend and backend are developed by different teams.
- You want to avoid over-fetching/under-fetching.
- Real-time features (like chat or notifications) are necessary using GraphQL subscriptions.
It’s especially useful in microservices environments, where data needs to be fetched from various services and assembled efficiently.
Conclusion
Both REST and GraphQL have their place in modern software development. REST is tried, true, and simple to implement ideal for many backend services, especially those with basic CRUD operations. GraphQL, on the other hand, offers greater flexibility and efficiency for data-rich frontends and complex apps.
The choice between REST and GraphQL isn’t always black and white. In some cases, teams even use both REST for some services and GraphQL as a data gateway or aggregator. Ultimately, the best approach depends on your specific project needs, team expertise, and future scalability plans.
