Understanding REST vs GraphQL
1. Comparing REST and GraphQL
| Aspect | REST | GraphQL |
|---|
| Endpoints | Many resource URIs | Single /graphql |
| HTTP methods | GET/POST/PUT/PATCH/DELETE | POST (mostly) |
| Data shape | Server-defined | Client-defined |
| Over/under-fetching | Common | Eliminated |
| Caching | HTTP-native | Application-layer (Apollo, urql) |
| Versioning | URI/header | Schema evolution + deprecation |
| Tooling | OpenAPI, Swagger | Introspection, Playground |
| Learning curve | Low | Higher |
| File uploads | Native multipart | multipart spec extension |
2. Handling Over-fetching with REST
| Technique | Notes |
|---|
| Sparse fieldsets | ?fields=id,name,email |
| Multiple endpoints | /users/summary vs /users/full |
| BFF aggregation | Per-client tailored payloads |
| Compression | Mitigates payload size cost |
3. Handling Under-fetching with REST
| Technique | Notes |
|---|
| Resource expansion | ?expand=author,comments |
| Composite endpoints | /dashboard aggregates many resources |
| Batch endpoints | Submit multiple ops in one request |
| HTTP/2 multiplexing | Cheap parallel requests |
4. Choosing REST for Simple CRUD
| REST Wins When | Reason |
|---|
| Resource-oriented domain | Maps cleanly to URIs |
| Heavy caching needs | HTTP cache infrastructure |
| Public APIs | Familiar, broad tooling |
| Simple client requirements | Predictable shapes |
| File uploads / streaming | HTTP-native |
5. Choosing GraphQL for Complex Data
| GraphQL Wins When | Reason |
|---|
| Many clients, varied needs | Each picks fields |
| Deeply nested relations | One query traverses graph |
| Mobile clients on slow networks | Minimize payload |
| Rapid frontend iteration | No backend change for new shapes |
| Aggregating microservices | Federation, schema stitching |
6. Implementing GraphQL on Top of REST
| Layer | Role |
|---|
| GraphQL gateway | Resolves fields by calling REST services |
| DataLoader | Batch + cache REST calls per request |
| Schema | Defined in gateway, independent of REST shapes |
| Migration path | Adopt GraphQL without rewriting backends |
7. Comparing Versioning Strategies
| Approach | REST | GraphQL |
|---|
| Style | Explicit versions (v1, v2) | Continuous evolution |
| Add field | Safe in any version | Safe (clients must request it) |
| Remove field | Major version bump | Mark @deprecated, monitor usage, then remove |
| Breaking change | New version | Avoided; new field/type added instead |
8. Comparing Caching Approaches
| Aspect | REST | GraphQL |
|---|
| Transport cache | HTTP (CDN, browser) | POST not cached by default |
| Workaround | Native | Persisted queries (GET + hash) |
| Per-entity cache | Per-URI | Normalized client cache (Apollo, Relay) |
| Invalidation | By URI | By entity ID + type |
9. Choosing the Right Approach
Decision Heuristics
- Pick REST for: public APIs, file/binary transfers, CDN-heavy workloads, simple resource models, IoT/embedded clients, server-to-server contracts.
- Pick GraphQL for: rich client UIs (web + mobile), aggregating multiple microservices, evolving schemas, minimizing mobile bandwidth, complex object graphs.
- Use both: REST for public/integrations + GraphQL gateway for internal apps. Common in mature platforms.
- Consider gRPC for service-to-service if performance and strong typing dominate.
Note: The choice is rarely binary — many production systems run REST and GraphQL side-by-side, picking the right tool per use case.