FrameworksDecision guide
REST
VS
GraphQL
Two API paradigms that have been argued about for a decade. The honest answer is that most teams should ship REST, some teams should ship GraphQL, and a small number should ship both. Here is how to tell which you are.
12
Pros
10
Cons
8
Best fits
4
Decision factors
Head to head
The full breakdown
Pros, cons, and ideal use cases for each option, side by side.
A
REST
Resource-based API design using HTTP methods and endpoints. The lingua franca of API development and the right default for most projects.
Pros
- Simple, well-understood, and easy to onboard new engineers onto
- Excellent caching support at every layer, see the edge caching playbook
- Works with any client and any HTTP-aware tool, no special libraries needed
- Easy to debug with curl, browser devtools, and basic logs
- Mature tooling and OpenAPI ecosystem for documentation and code generation
- Operationally simple, every reverse proxy and CDN already speaks REST
Cons
- Over-fetching and under-fetching are real, especially as endpoints proliferate
- Multiple requests for related data unless you build composite endpoints
- Versioning gets messy fast, and most teams pick a strategy too late
- No built-in schema unless you commit to OpenAPI, which not every team does
- Pagination, filtering, and sorting are reinvented per project
Best fits
- Simple CRUD APIs and admin tools
- Public APIs that need to be consumed by anyone with a fetch client
- Caching-heavy applications where HTTP semantics matter
- Server-to-server integrations in fintech
B
GraphQL
Query language for APIs enabling precise data fetching with strong typing. Common in mobile backends and frontends with diverse data needs.
Pros
- Request exactly the fields you need, no more, no less
- Single endpoint that simplifies routing and client setup
- Strong type system that powers excellent client tooling
- Introspection and schema-driven tooling for codegen and testing
- Great for complex UIs where one view stitches together many resources
- Federation and stitching make it viable across multiple backend teams
Cons
- Caching complexity, HTTP caches do not understand queries by default
- N+1 query problems are easy to write and easy to miss in review
- Learning curve for both server and client teams, especially around resolvers
- Overhead for simple APIs that would be five clean REST endpoints
- Authorisation at field level requires careful design or it gets verbose fast
Best fits
- Complex data requirements with many clients shaping the same data differently
- Mobile applications, see mobile development
- Rapidly evolving UIs where backend changes lag the frontend
- Multiple client types (web, mobile, partners) sharing one API
At a glance
Quick facts
The key dimensions side by side, so you do not have to scroll back and forth.
| Dimension | AREST | BGraphQL |
|---|---|---|
| Endpoint shape | Many resource endpoints | Single endpoint |
| Over-fetching | Common | Rare |
| Caching | HTTP-native, easy | Hard, query-aware |
| Type system | Optional (OpenAPI) | Required, schema-first |
| N+1 risk | Low | High, needs DataLoader |
| Tooling | Universal HTTP tools | Specific GraphQL tools |
| Learning curve | Gentle | Steeper |
| Fit for mobile | Good | Excellent |
The verdict
Ship REST by default. Reach for GraphQL when you have multiple clients with genuinely different data needs, or when one screen needs to stitch together five backends. Most teams do not, and they pay the GraphQL tax forever for a problem they never had.
Sri Vardhan
Other considerations
Before you decide
The questions I would ask before committing to either option.
Evaluate data fetching patterns in your existing apps
Consider client diversity and how much your screens actually overlap in data needs
Factor in caching requirements at edge and browser layers
Think about team expertise, GraphQL needs investment to do well
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Need a second opinion for your stack?
If this comparison is the start of a real decision rather than a quick read, I am happy to talk through your specific constraints.