Introduction
GraphQL vs REST is a common question when building APIs. Developers want to know which approach gives better performance, simpler client code, and easier evolution. This guide explains how each works, shows clear comparisons, and gives practical advice to choose the right API style for your project. Expect real-world examples, a clear decision checklist, and links to official docs.
What is REST?
REST (Representational State Transfer) is an architectural style that uses HTTP methods and resource URLs. Clients request resources via endpoints like /users or /orders/123. Responses typically return full JSON objects.
REST is simple and widely supported across tools and platforms. It relies on HTTP semantics like GET, POST, PUT, PATCH, and DELETE.
What is GraphQL?
GraphQL is a query language and runtime developed by Facebook. Clients request exactly the fields they need with a single endpoint, often /graphql. Servers resolve fields defined in a schema.
GraphQL centralizes schema, types, and validation. It supports nested queries and can reduce over-fetching and under-fetching of data.
How They Work: Quick View
- REST API: Multiple endpoints, each returns complete resources.
- GraphQL: Single endpoint, client defines data shape via queries.
Key Differences (At a Glance)
| Aspect | REST | GraphQL |
|---|---|---|
| Endpoint | Many resource URLs | One flexible endpoint |
| Over-/Under-fetching | Common | Minimized |
| Caching | HTTP caching easy | More complex, often needs custom strategies |
| Versioning | URI or header versions | No versioning; schema evolves |
| Real-time | Webhooks / WebSockets | Subscriptions built-in |
| Learning curve | Low | Moderate |
Detailed Comparison
1. API Performance
GraphQL can reduce round trips by letting clients fetch nested data in one request. This often improves perceived speed on mobile or high-latency networks. REST can perform well with well-designed endpoints and HTTP/2.
2. Caching
REST benefits from standard HTTP caching (ETag, Cache-Control). GraphQL needs extra work: query hashing, persisted queries, or edge caching with CDNs. For heavy-read apps, REST caching is easier to implement.
3. Real-time and Subscriptions
GraphQL supports subscriptions natively, which simplifies real-time features. REST relies on WebSockets, server-sent events, or polling. For live updates, GraphQL often requires less glue code.
4. Security
Both need auth, rate limiting, and input validation. GraphQL adds risks like expensive nested queries. Use query depth limits, query complexity scoring, and rate limits to protect GraphQL endpoints.
5. Versioning & Evolution
REST commonly uses versioned endpoints (v1, v2). GraphQL avoids versions by evolving the schema through deprecation. This can be cleaner but requires disciplined schema management.
6. Developer Experience
GraphQL offers strong introspection and typed schemas. Tools like GraphiQL and codegen boost productivity. REST benefits from familiar patterns and simpler tooling for simple CRUD APIs.
When to Choose GraphQL
- Clients need precise data shapes or many nested objects.
- Mobile apps where bandwidth and latency matter.
- Rapid front-end iteration with evolving UI data needs.
- When you want self-documenting schemas and strong type systems.
Example: A social feed that shows user profiles, posts, and comments. GraphQL lets the client fetch profile and nested comments in one request.
When to Choose REST
- Simple CRUD services with clear resource boundaries.
- Public APIs where caching and HTTP semantics are critical.
- Teams that need quick onboarding with minimal tooling.
Example: A public product catalog that benefits from CDN caching and predictable resource URLs.
Hybrid Approaches
Many teams use both: REST for file downloads and caching-heavy endpoints; GraphQL for rich, client-driven queries. You can also build a GraphQL layer that aggregates multiple REST services.
Migration Considerations
Strategies
- Start with GraphQL gateway while keeping REST services intact.
- Add persisted queries to improve caching and security.
- Deprecate REST endpoints gradually with metrics to guide removal.
Practical Steps
- Define a schema and map fields to existing REST calls.
- Implement caching and rate limits on the GraphQL gateway.
- Monitor query patterns to add optimizations or new endpoints.
Real-world Examples
Shop frontends often use GraphQL to fetch product details, inventory, and user cart in one request. Banking and regulatory systems sometimes favor REST for clear audit trails and HTTP-level caching.
Best Practices & Tips
- For GraphQL: enforce complexity limits, use persisted queries, and enable server-side caching layers.
- For REST: design resource URLs carefully and use proper HTTP status codes.
- For both: centralize auth, logging, and monitoring.
Comparison Table: Technical Trade-offs
| Trade-off | GraphQL | REST |
|---|---|---|
| Latency | Fewer round trips | Multiple requests possible |
| Bandwidth | Lower with exact fields | Higher, may include unused fields |
| Caching | Requires custom solutions | Built-in via HTTP |
| Complexity | Server resolver complexity | Endpoint proliferation |
Official Resources
Read GraphQL’s official docs at graphql.org for schema and tooling info. For REST concepts and HTTP semantics, see Mozilla’s documentation at MDN REST guide.
Quick Decision Checklist
- Need flexible queries and fewer requests? Pick GraphQL.
- Need easy caching and simple CRUD? Pick REST.
- Both fit? Use a hybrid or gateway approach.
Conclusion
GraphQL and REST both solve API needs but suit different problems. Use GraphQL for client-driven, nested data and fast iteration. Use REST when HTTP caching and simple resource semantics matter. Test with real traffic, protect your endpoints, and choose the pattern that reduces complexity for your team.