REST vs GraphQL — Which API Architecture Should You Use?
Compare REST and GraphQL API architectures. Understand over-fetching, under-fetching, flexibility, caching, and when each approach delivers better results.
| Feature | REST | GraphQL |
|---|---|---|
| Over-fetching | Common problem | Eliminated by design |
| Under-fetching | Requires multiple requests | Single request for complex data |
| Caching | Excellent (HTTP cache) | Complex (requires CDN config) |
| Type System | Optional (OpenAPI) | Built-in, enforced |
| Versioning | URL versioning (v1, v2) | Schema evolution (deprecate fields) |
| Learning Curve | Low | Medium-High |
| Real-time Data | SSE or WebSocket add-ons | Subscriptions built in |
| Best For | Public APIs, simple CRUD | Complex frontends, mobile |
Verdict
REST is the right default for public APIs, simple CRUD services, and teams new to API design. GraphQL excels when you have complex, data-intensive UIs (like a social feed or dashboard), multiple client types with different data needs, or when frontend teams need the autonomy to evolve their queries without backend changes.
The Over-Fetching Problem That Made GraphQL Famous
Facebook created GraphQL in 2012 to solve a specific problem: their mobile news feed needed to render different data for different device types, but REST endpoints returned fixed data shapes that included far more fields than mobile clients needed. Loading a user profile might return 50 fields when the UI only displayed 8. Over millions of requests on slow mobile connections, this wasted bandwidth was measurably impacting app performance. GraphQL's solution — let the client specify exactly which fields to return — directly addressed this. If your application has this problem (multiple client types with different data needs, bandwidth-constrained environments), GraphQL is genuinely compelling.
HTTP Caching: REST's Hidden Advantage
REST's reliance on HTTP semantics gives it a powerful caching advantage that's often underappreciated. GET requests are cacheable at every layer: browser caches, CDN edge nodes, reverse proxies, and API gateways all understand HTTP cache headers. A popular product detail page might be served from CDN cache without ever hitting your application servers. GraphQL queries are typically sent as POST requests (to handle complex query bodies), which HTTP intermediaries don't cache by default. While solutions exist (persisted queries, GET for simple queries, CDN rules), they add operational complexity. For read-heavy public APIs, REST's caching benefits can dramatically reduce infrastructure costs.
Real-World Adoption Patterns
The industry has largely settled into pragmatic patterns. Public APIs with diverse third-party consumers (developer ecosystems, partner integrations) strongly favor REST for its simplicity and cacheability. Internal APIs for complex web applications, especially those with React-based dashboards or mobile apps needing rich data, increasingly use GraphQL (Apollo, Relay) or newer alternatives like tRPC for type-safe TypeScript stacks. The trend toward tRPC in the TypeScript ecosystem is worth noting: it provides GraphQL-like type safety and request efficiency while keeping REST's simplicity, suggesting that the core goal (type-safe, efficient client-server communication) can be achieved with different technical approaches.
Frequently Asked Questions
Yes, many applications do. A common pattern is to use REST for public API endpoints (where caching and simplicity matter) and GraphQL for internal client-to-backend communication where frontend teams need query flexibility.
The N+1 problem occurs when a GraphQL resolver fetches a list of N items, then makes N additional database queries to fetch related data for each item. For example, fetching 100 posts and then making 100 separate queries for their authors. The solution is DataLoader (by Facebook), which batches and deduplicates queries.
Often yes. Mobile apps have variable network conditions where minimizing payload size and request count matters significantly. GraphQL's ability to fetch exactly the fields needed in a single request reduces data transfer and latency, improving perceived performance on mobile networks.
No, and the industry has stabilized with both in widespread use. REST dominates public APIs (Stripe, GitHub, Twilio all offer REST). GraphQL is popular for internal APIs, BFF (Backend-For-Frontend) patterns, and complex data platforms. GitHub offers both REST and GraphQL APIs.