REST (Representational State Transfer) and GraphQL are both architectural approaches for building web APIs, but they differ fundamentally in how clients request and receive data. REST organizes APIs around resources, where each resource (users, posts, comments) has its own URL endpoint and responds with a fixed data shape. Clients use standard HTTP methods (GET, POST, PUT, DELETE) to perform operations. GraphQL, developed by Facebook and open-sourced in 2015, provides a single endpoint where clients send queries that specify exactly which fields and relationships they need, receiving only that data in response.
The over-fetching and under-fetching problem drove GraphQL's creation. A REST endpoint like /api/users/123 might return 30 fields when the client only needs name and email. Conversely, displaying a user profile with their posts and followers requires three separate REST requests (/users/123, /users/123/posts, /users/123/followers). GraphQL solves both problems with a single query that specifies exactly the needed fields across related resources, receiving one precisely-shaped response.
REST leverages the entire HTTP protocol. Status codes (200, 404, 500) communicate results. Cache-Control headers enable CDN and browser caching without application code. ETags support conditional requests. Content negotiation via Accept headers allows format flexibility. This tight integration with HTTP means REST APIs get infrastructure-level features for free. GraphQL operates over HTTP but uses POST for everything and always returns 200 status, moving error handling and caching into the application layer.
Type safety is another differentiator. Every GraphQL API has a schema written in the Schema Definition Language (SDL) that defines all types, fields, relationships, and operations. This schema serves as documentation, enables auto-completion in editors like GraphiQL, generates TypeScript types for frontend code, and validates queries before execution. REST APIs can achieve similar type safety through OpenAPI/Swagger specifications, but this is optional and often incomplete in practice.
| Feature | REST | GraphQL |
|---|---|---|
| Data fetching | Multiple endpoints, fixed response shapes | Single endpoint, client specifies exact fields |
| Over-fetching | Common, endpoints return full resource | Eliminated, client requests only needed fields |
| Under-fetching | Requires multiple requests for related data | Single query fetches nested related resources |
| Caching | HTTP caching built-in (ETags, Cache-Control) | Complex, requires custom caching strategies |
| Learning curve | Low, uses standard HTTP methods | Higher, requires learning schema and query language |
| API versioning | URL versioning (/v1/, /v2/) is straightforward | Versionless, evolve schema with deprecation |
| Error handling | HTTP status codes are standardized and clear | Always returns 200, errors embedded in response body |
| File uploads | Multipart form data is well-supported | Not natively supported, requires workarounds |
| Real-time data | Requires WebSockets or SSE alongside REST | Built-in subscriptions for real-time updates |
| Tooling maturity | Postman, Swagger, OpenAPI (very mature) | Apollo, GraphiQL, Relay (growing rapidly) |
| Type safety | Optional via OpenAPI spec | Intrinsic, schema is the type system |
| Rate limiting | Easy per-endpoint rate limiting | Complex, must analyze query cost/depth |
Use REST for simple CRUD APIs, public APIs where HTTP caching matters, file-heavy operations, and teams with limited GraphQL experience. Choose GraphQL for applications with complex data relationships, mobile apps that need bandwidth efficiency, and internal APIs where multiple frontend teams consume the same data differently.
Evaluate your data complexity and consumption patterns. If your API serves simple CRUD operations where clients typically need full resources (create a user, get an order, update a product), REST's simplicity is an advantage. If your data model has deep relationships and different clients (web dashboard, mobile app, third-party integrations) need different slices of the same data, GraphQL's flexible queries reduce frontend complexity and network requests.
Consider your caching requirements. REST APIs benefit enormously from HTTP caching infrastructure: CDNs cache GET responses, browsers respect Cache-Control headers, and reverse proxies like Varnish work out of the box. GraphQL POST requests are not cacheable at the HTTP layer, requiring application-level caching solutions like Apollo Client's normalized cache or persisted queries. For public APIs serving high-traffic read-heavy workloads, REST's caching story is significantly simpler.
Assess your team's experience and tooling investment. REST is understood by virtually every developer and supported by every HTTP tool (curl, Postman, browser). GraphQL requires learning the query language, understanding resolvers, and adopting specialized tooling. The initial investment pays off in complex applications but adds overhead for simple APIs. If your team is building their first API, REST provides a faster path to production.
Think about security and rate limiting. REST APIs can be rate-limited per endpoint, and each endpoint has a predictable computation cost. GraphQL queries can be arbitrarily complex, potentially triggering expensive database joins across multiple tables in a single request. Protecting a GraphQL API requires query complexity analysis, depth limiting, and cost-based rate limiting, which are more complex to implement than per-route throttling. Test your API responses with PinusX's JSON Formatter to inspect response payloads without sending data to any server.
No. GraphQL adds complexity that is not justified for simple CRUD APIs. REST excels for file uploads, simple resource operations, public APIs that benefit from HTTP caching, and teams without GraphQL experience. GraphQL shines for complex data relationships, mobile apps needing bandwidth efficiency, and internal APIs serving multiple frontends with different data needs.
Yes, many organizations run both. A common pattern is using REST for simple CRUD operations and file handling while using GraphQL for complex data fetching across related entities. Some teams wrap existing REST APIs with a GraphQL layer using tools like Apollo Federation or Hasura to get GraphQL benefits without rewriting backend services.
No. REST remains the dominant API style for public APIs, simple microservices, and file-based operations. GraphQL adoption is growing for complex applications and internal APIs, but REST is simpler, more cacheable, and better understood. The industry is not converging on one style but rather using each where its strengths apply.
GraphQL requires more security consideration because clients can construct arbitrarily complex queries. Without proper depth limiting, query cost analysis, and field-level authorization, a single GraphQL query could trigger expensive database operations or expose unauthorized data. REST's fixed endpoints make security boundaries clearer and rate limiting simpler.
The GraphQL specification does not include file uploads. The community-standard approach is the GraphQL Multipart Request Specification, which uses multipart form data to upload files alongside a GraphQL mutation. Some teams use a separate REST endpoint for file uploads and reference the uploaded file in subsequent GraphQL mutations.
Get instant alerts when your endpoints go down. 60-second checks, free forever.
Start Monitoring Free →