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REST vs GraphQL: API Architecture Comparison (2026)

DodaTech Updated 2026-06-23 5 min read

In this tutorial, you'll learn about REST vs GraphQL: API Architecture Comparison (2026). We cover key concepts, practical examples, and best practices to help you understand and apply this topic effectively.

REST and GraphQL are the two dominant API architectures, each solving data fetching differently. This comparison covers over-fetching, under-fetching, caching, tooling, and real-world performance to help you choose between REST and GraphQL for your next API.

graph LR
  A[Client Request] --> B{REST or GraphQL?}
  B -->|REST| C[Multiple Endpoints]
  C --> D[Fixed Response Shape]
  C --> E[HTTP Caching]
  B -->|GraphQL| F[Single Endpoint]
  F --> G[Client-defined Response]
  F --> H[No Built-in Caching]
  style B fill:#ff6c37,color:#fff
  style C fill:#25a162,color:#fff
  style F fill:#e535ab,color:#fff

At a Glance

Feature REST GraphQL
Endpoint Structure Multiple (resources) Single (/GraphQL)
Data Fetching Fixed response per endpoint Client queries exactly what needed
Over-fetching Common None
Under-fetching Common (requires N+1 requests) None
Caching HTTP caching (native) Manual (Apollo, Relay)
Versioning URL versioning (/v1/) Evolve schema (no versioning)
Learning Curve Gentle Moderate
Tooling curl, Postman, any HTTP client GraphiQL, Apollo DevTools
File Upload Multipart form data Complex (base64 or multipart)
Real-time WebSocket (separate) Subscriptions (built-in)

Data Fetching Comparison

The most significant difference: REST returns fixed data shapes per endpoint, often over-fetching or requiring multiple requests. GraphQL lets the client request exactly the data it needs in a single request.

// REST — multiple endpoints for related data
async function getDashboardDataREST(userId) {
  const user = await fetch(`/api/users/${userId}`).then(r => r.json());
  // Response includes: id, name, email, address, phone, role, createdAt, updatedAt...
  // You probably only need name and email, but REST returns everything

  const posts = await fetch(`/api/users/${userId}/posts`).then(r => r.json());
  // Returns all post fields: id, title, body, createdAt, comments, likes...
  // You might only need title and date

  const followers = await fetch(`/api/users/${userId}/followers`).then(r => r.json());
  // Third request for related data

  return { user, posts, followers };
  // Three round trips, over-fetched on each
}
# GraphQL — single request, exact data
query GetDashboard($userId: ID!) {
  user(id: $userId) {
    name
    email
    posts {
      title
      createdAt
    }
    followers {
      name
      avatarUrl
    }
  }
}

Expected response:

{
  "data": {
    "user": {
      "name": "Jane Doe",
      "email": "jane@example.com",
      "posts": [
        { "title": "GraphQL vs REST", "createdAt": "2026-06-20" },
        { "title": "API Design Tips", "createdAt": "2026-06-15" }
      ],
      "followers": [
        { "name": "Alice", "avatarUrl": "/avatars/alice.jpg" }
      ]
    }
  }
}

Server Implementation

REST servers define fixed routes with controller functions. GraphQL servers define a schema with resolvers that can fetch data from any source.

# REST API with FastAPI
from fastapi import FastAPI, HTTPException
from typing import List

app = FastAPI()

@app.get("/api/users/{user_id}")
async def get_user(user_id: int):
    user = await db.fetch_one("SELECT * FROM users WHERE id = ?", user_id)
    if not user:
        raise HTTPException(status_code=404, detail="User not found")
    return user  # Always returns all user fields

@app.get("/api/users/{user_id}/posts")
async def get_user_posts(user_id: int):
    posts = await db.fetch_all("SELECT * FROM posts WHERE author_id = ?", user_id)
    return posts  # Always returns all post fields
# GraphQL API with Strawberry
import strawberry
from typing import List, Optional

@strawberry.type
class User:
    id: int
    name: str
    email: str

    @strawberry.field
    async def posts(self) -> List["Post"]:
        # Only called if client requests posts field
        return await db.fetch_all(
            "SELECT id, title, created_at FROM posts WHERE author_id = ?", self.id
        )

@strawberry.type
class Query:
    @strawberry.field
    async def user(self, id: int) -> Optional[User]:
        return await db.fetch_one(
            "SELECT id, name, email FROM users WHERE id = ?", id
        )

schema = strawberry.Schema(query=Query)

Caching Strategies

REST leverages HTTP caching (ETags, Cache-Control, CDN caching) natively. GraphQL requires manual caching with libraries like Apollo Client or Relay.

// REST — HTTP caching with ETags
const response = await fetch("/api/users/1", {
  headers: { "If-None-Match": '"abc123"' }
});

if (response.status === 304) {
  // Use cached data — server says nothing changed
  console.log("Using cached user data");
} else {
  const user = await response.json();
  // Cache the ETag for next request
  const etag = response.headers.get("ETag");
  localStorage.setItem("user-etag", etag);
  console.log("Fresh user data:", user);
}
// GraphQL — Apollo Client caching
import { ApolloClient, InMemoryCache, gql } from "@apollo/client";

const client = new ApolloClient({
  uri: "/graphql",
  cache: new InMemoryCache({
    typePolicies: {
      User: {
        fields: {
          posts: {
            merge(existing = [], incoming) {
              return incoming; // Replace cache on new fetch
            }
          }
        }
      }
    }
  })
});

// Cache policies: cache-first, network-only, cache-and-network, etc.
const { data } = await client.query({
  query: gql`
    query GetUser($id: ID!) {
      user(id: $id) { name email }
    }
  `,
  variables: { id: "1" },
  fetchPolicy: "cache-first"
});

Bottom Line

Choose REST for simple CRUD APIs, public-facing services where HTTP caching matters, file uploads, or when working with teams new to API development. Choose GraphQL for complex data requirements, mobile applications where bandwidth matters, dashboard UIs with varied data needs, or when frontend teams need control over data shapes.

Practice Questions

  1. What problem does GraphQL solve that REST does not address well?
  2. How does caching differ between REST and GraphQL?
  3. Which API architecture would you choose for a public weather API and why?

FAQ

{{< faq "Can I use REST and Graphql together?">}} Yes. Many organizations run both — REST for public APIs (simple, cacheable) and GraphQL for internal or mobile clients (flexible queries). Tools like Apollo Federation can stitch REST endpoints into a unified GraphQL schema. {{< /faq >}}

{{< faq "Is Graphql faster than REST?">}} GraphQL can be faster for complex UIs because it eliminates multiple round trips and over-fetching. For simple endpoints with fixed data needs, REST is typically faster due to HTTP caching and lower parsing overhead. Performance depends on the specific use case. {{< /faq >}}

Which is better for microservices?

REST is more common in Microservices due to its simplicity and stateless nature. GraphQL is typically used as a BFF (Backend For Frontend) layer that aggregates multiple Microservices into a single endpoint for client consumption.


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