core
Request shape
depends
REST
Many endpoints, one per resource; the server decides the response shape.
GraphQL
One endpoint; the client specifies exactly which fields and relations it wants.
APIs · Updated 2026-06-05
REST vs GraphQL
REST is the right default for most APIs: it is simple, cacheable over plain HTTP, and every tool understands it. GraphQL earns its complexity when clients are diverse and over-fetching is real — many screens, many shapes, one graph. Plenty of teams run both: REST for public/simple surfaces, GraphQL for a rich client app.
REST models the server as a set of resources you act on with HTTP verbs. GraphQL models it as one typed graph the client queries for exactly the fields it wants. The trade is over-fetching and round-trips (REST’s weak spots) against caching simplicity and operational maturity (GraphQL’s).
Quick takes
If you're…
- You have a simple CRUD API with stable, predictable responses REST REST endpoints map cleanly to resources and cache for free over HTTP.
- Mobile and web clients each need different subsets of the same data GraphQL One GraphQL query fetches exactly the fields each client needs — no over- or under-fetching.
- You rely heavily on HTTP/CDN caching REST GET URLs cache trivially; GraphQL POSTs to one endpoint do not.
- A screen aggregates data from many resources GraphQL GraphQL collapses several REST round-trips into a single request.
- You are publishing a public API for third parties REST REST is universally understood and easier to document, version, and rate-limit per endpoint.
- Your frontend changes shape often and you want fewer backend changes GraphQL Clients add or drop fields without new endpoints, as long as the schema covers them.
Decision wizard
A few questions, a verdict.
At a glance
The scorecard.
Dimension
REST
GraphQL
Edge
In depth
Dimension by dimension.
core
Over/under-fetching
edge: GraphQL
REST
Common: endpoints return fixed payloads, so clients often get too much or need several calls.
GraphQL
Solved by design: one query returns precisely the requested fields across resources.
ops
Caching
edge: REST
REST
Trivial: GET responses cache in browsers, CDNs, and proxies by URL.
GraphQL
Harder: queries POST to one URL; needs client-side normalized caches (Apollo, urql) or persisted queries.
features
Schema & typing
edge: GraphQL
REST
No built-in schema; OpenAPI/Swagger adds one as a layer.
GraphQL
A typed schema is mandatory and introspectable, powering codegen and tooling out of the box.
ops
Versioning
edge: GraphQL
REST
Usually explicit (/v1, /v2) — clear but proliferates endpoints.
GraphQL
Evolutionary: add fields freely, deprecate old ones; clients pull only what they use.
core
Backend performance risk
edge: REST
REST
Predictable per endpoint; easy to reason about and rate-limit.
GraphQL
N+1 resolver problems and expensive nested queries need dataloaders, depth limits, and cost analysis.
ecosystem
Tooling & ubiquity
edge: REST
REST
Universal: curl, browsers, every HTTP client and gateway speaks it.
GraphQL
Excellent but narrower: GraphiQL, Apollo, codegen — strongest inside app teams.
When to pick neither
A different shape of problem.
- Internal service-to-service calls where you control both ends and want speed
- A TypeScript monorepo wanting end-to-end types without a schema language
- JSON:APIYou want REST with a strict convention for includes and sparse fieldsets
Situational picks
For specific cases.
A public API for third-party developers
REST
Universality, per-endpoint rate limiting, and easy caching matter more than query flexibility.
A data-rich SPA or mobile app with many views
GraphQL
Per-screen queries kill over-fetching and cut round-trips; the typed schema speeds the client team.
A small internal CRUD service
REST
REST is less machinery to run; GraphQL’s caching and N+1 concerns are not worth it here.
A platform serving both partners and a first-party app
Either
REST for the public surface, GraphQL for the internal client, is a common and healthy split.
Sources
Primary material.
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