GraphQL vs REST: What Are They?
REST (Representational State Transfer) and GraphQL are the two dominant paradigms for building APIs. REST, introduced by Roy Fielding in 2000, uses standard HTTP methods and resource-based URLs. GraphQL, created by Facebook in 2015, uses a single endpoint with a flexible query language that lets clients request exactly the data they need.
Both approaches have trade-offs. REST is simpler to implement and widely understood, while GraphQL provides more flexibility for complex data requirements. This guide compares both in depth to help you choose the right approach for your project.
Core Architecture Differences
REST Architecture:
- Multiple endpoints (one per resource)
- HTTP methods define operations (GET, POST, PUT, DELETE)
- Server decides response shape
- Stateless, cacheable by default
GET /api/users/123 -> Get user
GET /api/users/123/posts -> Get user's posts
POST /api/users -> Create user
PUT /api/users/123 -> Update user
DELETE /api/users/123 -> Delete user
GraphQL Architecture:
- Single endpoint (/graphql)
- POST method for all operations
- Client decides response shape via queries
- Queries, mutations, and subscriptions
POST /graphql
{
query: "{ user(id: 123) { name email posts { title } } }"
}Data Fetching: Over-fetching and Under-fetching
One of the key differences between REST and GraphQL is how they handle data fetching. REST endpoints often return fixed data structures, which can lead to over-fetching (getting more data than needed) or under-fetching (needing multiple requests to get all required data).
REST Example: Multiple Requests Needed
// REST: Need 3 requests to build a user profile page
// Request 1: Get user
const user = await fetch('/api/users/123');
// Response: { id: 123, name: "Alice", email: "alice@example.com",
// bio: "...", avatar: "...", createdAt: "...",
// settings: {...}, /* lots of extra fields */ }
// Request 2: Get user's posts
const posts = await fetch('/api/users/123/posts');
// Response: [{ id: 1, title: "...", body: "...", /* extra fields */ }]
// Request 3: Get user's followers count
const followers = await fetch('/api/users/123/followers?count=true');
// Response: { count: 1234 }
// Problem: 3 round trips, over-fetching unused fieldsGraphQL Example: Single Request
# GraphQL: One request, exactly the data you need
query UserProfile {
user(id: 123) {
name
email
avatar
posts(limit: 5) {
title
createdAt
}
followersCount
}
}
# Response:
# {
# "data": {
# "user": {
# "name": "Alice",
# "email": "alice@example.com",
# "avatar": "https://...",
# "posts": [
# { "title": "My First Post", "createdAt": "2026-01-15" }
# ],
# "followersCount": 1234
# }
# }
# }Schema and Type System
GraphQL has a built-in type system that serves as documentation and validation. REST APIs typically use OpenAPI (Swagger) for similar functionality, but it is not built into the protocol.
# GraphQL Schema Definition Language (SDL)
type User {
id: ID!
name: String!
email: String!
avatar: String
posts(limit: Int = 10, offset: Int = 0): [Post!]!
followersCount: Int!
createdAt: DateTime!
}
type Post {
id: ID!
title: String!
body: String!
author: User!
tags: [String!]!
publishedAt: DateTime
}
type Query {
user(id: ID!): User
users(filter: UserFilter, limit: Int = 20): [User!]!
post(id: ID!): Post
searchPosts(query: String!): [Post!]!
}
type Mutation {
createUser(input: CreateUserInput!): User!
updateUser(id: ID!, input: UpdateUserInput!): User!
deleteUser(id: ID!): Boolean!
createPost(input: CreatePostInput!): Post!
}
input CreateUserInput {
name: String!
email: String!
avatar: String
}
type Subscription {
postCreated: Post!
userOnline(userId: ID!): Boolean!
}Implementation Examples
REST API with Express.js
const express = require('express');
const app = express();
// GET /api/users/:id
app.get('/api/users/:id', async (req, res) => {
const user = await db.users.findById(req.params.id);
if (!user) return res.status(404).json({ error: 'Not found' });
res.json(user);
});
// GET /api/users/:id/posts
app.get('/api/users/:id/posts', async (req, res) => {
const { limit = 10, offset = 0 } = req.query;
const posts = await db.posts.findByUserId(req.params.id, { limit, offset });
res.json(posts);
});
// POST /api/users
app.post('/api/users', async (req, res) => {
const user = await db.users.create(req.body);
res.status(201).json(user);
});
// PUT /api/users/:id
app.put('/api/users/:id', async (req, res) => {
const user = await db.users.update(req.params.id, req.body);
res.json(user);
});
// DELETE /api/users/:id
app.delete('/api/users/:id', async (req, res) => {
await db.users.delete(req.params.id);
res.status(204).send();
});GraphQL API with Apollo Server
const { ApolloServer } = require('@apollo/server');
const { startStandaloneServer } = require('@apollo/server/standalone');
const typeDefs = `
type User {
id: ID!
name: String!
email: String!
posts(limit: Int = 10): [Post!]!
}
type Post {
id: ID!
title: String!
author: User!
}
type Query {
user(id: ID!): User
users: [User!]!
}
type Mutation {
createUser(name: String!, email: String!): User!
}
`;
const resolvers = {
Query: {
user: (_, { id }) => db.users.findById(id),
users: () => db.users.findAll(),
},
Mutation: {
createUser: (_, { name, email }) => db.users.create({ name, email }),
},
User: {
// Resolver for nested posts field
posts: (parent, { limit }) => db.posts.findByUserId(parent.id, { limit }),
},
Post: {
author: (parent) => db.users.findById(parent.authorId),
},
};
const server = new ApolloServer({ typeDefs, resolvers });
const { url } = await startStandaloneServer(server, { listen: { port: 4000 } });Comprehensive Comparison
Feature REST GraphQL
------- ---- -------
Endpoints Multiple (/users, /posts) Single (/graphql)
Data fetching Fixed response shape Client-specified fields
Over-fetching Common problem Solved by design
Under-fetching Multiple requests needed Single query
Caching HTTP caching (simple) Complex (query-based)
File uploads Native support Requires extra setup
Error handling HTTP status codes 200 + errors array
Versioning URL (/v1/, /v2/) or headers Schema evolution
Learning curve Lower Higher
Tooling Postman, curl, Swagger GraphiQL, Apollo Studio
Real-time WebSocket / SSE (separate) Subscriptions (built-in)
Rate limiting Simple (per endpoint) Complex (query complexity)
Documentation OpenAPI/Swagger Self-documenting schema
N+1 problem Managed on server DataLoader required
Browser caching GET requests cacheable Needs persisted queries
Monitoring Standard HTTP metrics Query-level analysis neededWhen to Choose REST
- Simple CRUD operations -- when resources map cleanly to endpoints
- Public APIs -- REST is universally understood and easy to consume
- Heavy caching needs -- HTTP caching works out of the box with GET requests
- File upload/download -- REST handles binary data natively
- Microservices communication -- simpler service-to-service calls
- Team familiarity -- most developers already know REST
- Webhook integrations -- external services expect REST endpoints
When to Choose GraphQL
- Complex data requirements -- multiple related entities in one request
- Mobile applications -- minimize data transfer and round trips
- Multiple client types -- web, mobile, and IoT need different data shapes
- Rapid frontend iteration -- frontend can change queries without backend changes
- Real-time features -- built-in subscription support
- Aggregating multiple data sources -- GraphQL as a gateway
- Strong typing requirements -- schema provides automatic type safety
Common Patterns: REST API Best Practices
// REST Best Practices
// 1. Use proper HTTP methods
GET /api/users // List users
POST /api/users // Create user
GET /api/users/:id // Get one user
PUT /api/users/:id // Full update
PATCH /api/users/:id // Partial update
DELETE /api/users/:id // Delete user
// 2. Use proper status codes
200 // OK
201 // Created
204 // No Content (successful delete)
400 // Bad Request (validation error)
401 // Unauthorized
403 // Forbidden
404 // Not Found
409 // Conflict
422 // Unprocessable Entity
429 // Too Many Requests
500 // Internal Server Error
// 3. Pagination
GET /api/users?page=2&limit=20
// Response: { data: [...], meta: { total: 100, page: 2, limit: 20 } }
// 4. Filtering and sorting
GET /api/users?role=admin&sort=-createdAt&fields=name,email
// 5. Error response format
{
"error": {
"code": "VALIDATION_ERROR",
"message": "Invalid email format",
"details": [{ "field": "email", "message": "Must be a valid email" }]
}
}Common Patterns: GraphQL Best Practices
// GraphQL Best Practices
// 1. Use DataLoader to solve N+1 problem
const DataLoader = require('dataloader');
const userLoader = new DataLoader(async (userIds) => {
const users = await db.users.findByIds(userIds);
return userIds.map(id => users.find(u => u.id === id));
});
// In resolver
Post: {
author: (post) => userLoader.load(post.authorId),
}
// 2. Query complexity limiting
const { createComplexityLimitRule } = require('graphql-validation-complexity');
const complexityLimit = createComplexityLimitRule(1000);
// 3. Pagination with cursor-based connections
type Query {
users(first: Int, after: String): UserConnection!
}
type UserConnection {
edges: [UserEdge!]!
pageInfo: PageInfo!
}
type UserEdge {
node: User!
cursor: String!
}
type PageInfo {
hasNextPage: Boolean!
endCursor: String
}Hybrid Approach: REST + GraphQL
Many successful companies use both REST and GraphQL in their architecture. A common pattern is to use GraphQL for client-facing APIs and REST for service-to-service communication and third-party integrations.
Hybrid Architecture Example:
[Mobile App] --> [GraphQL Gateway] --> [User Service (REST)]
[Web App] --> [GraphQL Gateway] --> [Post Service (REST)]
[3rd Party] --> [REST Public API] --> [Auth Service (REST)]
--> [ML Service (gRPC)]
Benefits:
- GraphQL for flexible client queries
- REST for simple microservice communication
- gRPC for high-performance internal calls
- Public REST API for third-party integrationsFrequently Asked Questions
Is GraphQL faster than REST?
Not inherently. GraphQL can be faster for complex pages that would require multiple REST calls, since it consolidates them into a single request. However, a well-designed REST API with specific endpoints can be just as fast or faster for simple operations due to HTTP caching advantages.
Does GraphQL replace REST?
No. GraphQL is an alternative, not a replacement. Many organizations use both. REST remains the better choice for simple APIs, public APIs, file handling, and service-to-service communication. GraphQL shines when clients need flexible data fetching.
Is GraphQL harder to learn?
Yes, GraphQL has a steeper learning curve. You need to understand schemas, resolvers, query language syntax, and concepts like the N+1 problem. REST leverages HTTP concepts that most developers already know. However, GraphQL tooling (GraphiQL, Apollo DevTools) makes the learning experience smoother.
How do you handle authentication in GraphQL?
Authentication in GraphQL works similarly to REST. Use JWT tokens or session cookies sent via HTTP headers. The token is validated in middleware or a context function before resolvers execute. Authorization (who can access what) is typically handled at the resolver level or with directive-based approaches.
Related Tools and Guides
- JSON Formatter - Format and validate API responses
- JWT Decoder - Decode API authentication tokens
- REST API Best Practices - Complete REST design guide
- API Authentication Guide - OAuth, JWT, and API keys
- HTTP Status Codes Reference - Complete status code guide