REST API vs GraphQL — Which API Design Should You Choose

REST organizes your API around resources, each identified by a URL. You interact with resources using standard HTTP methods — GET to read, POST to create, PUT to update, DELETE to remove. Each endpoint returns a fixed data structure, and the server decides what fields to include in the response. This resource-oriented design is intuitive and maps cleanly to CRUD operations.

REST's simplicity is its greatest advantage. HTTP caching works out of the box because each URL represents a cacheable resource. Status codes communicate success and failure consistently. Any HTTP client can consume a REST API without special libraries. The pattern is so well-understood that most developers can design and consume REST APIs with minimal learning.

The main limitation of REST is over-fetching and under-fetching. A user profile endpoint might return 30 fields when the client only needs three. Conversely, displaying a dashboard might require calls to five different endpoints to assemble all the data, creating a waterfall of network requests that degrades performance, especially on mobile connections.

GraphQL uses a single endpoint and lets the client specify exactly what data it needs through a query language. Instead of hitting multiple REST endpoints, the client sends a single query that describes the shape of the desired response. The server resolves the query and returns precisely the requested data — no over-fetching, no under-fetching.

The schema is the foundation of GraphQL. It defines every type, field, and relationship in your API as a strongly-typed contract. This schema serves as living documentation, enables automatic code generation for client-side type safety, and powers developer tools like GraphQL Playground that let you explore and test queries interactively.

GraphQL also handles mutations for writes and subscriptions for real-time updates. Mutations use the same query language to send data to the server, and subscriptions establish WebSocket connections for push-based updates. This unified approach means one technology covers reading, writing, and real-time data — capabilities that would require REST plus WebSockets plus SSE in a traditional setup.

GraphQL's flexibility introduces complexity on the server side. Implementing a GraphQL server requires defining resolvers for every field, handling nested query performance through techniques like DataLoader to avoid N+1 query problems, and implementing query complexity analysis to prevent clients from requesting expensive deeply-nested data. These are solvable challenges, but they add development overhead.

Caching is harder with GraphQL because all requests go to a single endpoint via POST. Standard HTTP caching based on URL does not apply. You need client-side caching libraries like Apollo Client or urql, which maintain a normalized cache that tracks entities across queries. This works well but adds client-side complexity compared to REST's straightforward HTTP caching.

REST's simplicity makes it the better choice for public APIs consumed by third-party developers, for simple CRUD applications, and for teams without GraphQL experience. The learning curve of GraphQL — schemas, resolvers, query optimization, client caching — is non-trivial, and the benefits only justify that investment when your application has complex data relationships or diverse client requirements.

Choose REST when your API is resource-oriented with simple data relationships, when you need maximum HTTP caching efficiency, or when you are building a public API that prioritizes ease of consumption. REST is also the better choice for server-to-server communication where the data shape is stable and agreed upon by both parties.

Choose GraphQL when your frontend needs to display data from multiple related entities, when you have multiple clients with different data requirements, or when reducing network requests is critical for performance. GraphQL shines in SaaS dashboards, mobile applications with limited bandwidth, and products where the frontend evolves faster than the backend.

At Anubiz Labs, we implement REST APIs for most projects using NestJS with OpenAPI documentation. When the project's data complexity warrants it, we add GraphQL alongside REST rather than replacing it entirely. This hybrid approach gives you REST's simplicity for straightforward operations and GraphQL's flexibility for complex data fetching. Let us design the API architecture that best serves your product and users.