Skip to main content
Back to Blog
EngineeringJan 28, 2026·8 min read

GraphQL vs REST: Which Should You Choose?

A deep dive into the pros and cons of both API paradigms and how to pick the right one.

APIBackend
GraphQL vs REST showdown

Few engineering debates generate more heat than GraphQL vs REST. Both camps have legitimate arguments. Both have real-world success stories at massive scale. The framing of the question as "which is better?" is the wrong one — the right question is "which is better for this specific use case?"

REST: Why It's Still the Right Default

REST's strength is its simplicity and ubiquity. Every HTTP client in every language can consume a REST API without a specialised library. Caching at the CDN layer is trivial — a GET to /products/123 can be cached globally with standard HTTP headers. Browser DevTools, curl, Postman — all work natively. For public APIs consumed by third parties you don't control, REST is still the only sensible choice.

The genuine problem REST has is over-fetching and under-fetching. A mobile client displaying a user card might need name, avatar, and follower count — but the /users/:id endpoint returns 40 fields. Multiple endpoints mean multiple round trips. For teams with a single, controlled frontend, this is manageable. For teams with many frontends (iOS, Android, web, partner integrations) needing different data shapes from the same resources, REST's rigidity becomes expensive to maintain.

GraphQL: Where It Genuinely Shines

Over-fetching vs precise query comparison

GraphQL's type system and query language eliminate over/under-fetching entirely — clients request exactly the fields they need. A single GraphQL endpoint replaces dozens of REST routes. Schema introspection enables excellent developer tooling (GraphiQL, Apollo Studio) and auto-generated documentation. For complex, highly relational data — think social graphs, content management, e-commerce catalogs — GraphQL produces dramatically cleaner client code.

The costs are real: no native HTTP caching (requires persisted queries or a CDN with query-aware caching), N+1 query problems require DataLoader to solve, schema design requires significant upfront thought, and the learning curve for REST-trained developers is non-trivial.

Our Decision Framework

  • Public / partner API: REST always. Third parties expect it.
  • Internal API with one frontend: REST with BFF pattern.
  • Internal API with 3+ frontends needing different data shapes: GraphQL.
  • Highly relational data, complex filtering: GraphQL.
  • Simple CRUD operations, file uploads, webhooks: REST.