Rest vs GraphQL

Pranav Bakare - Sep 8 - - Dev Community

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REST (Representational State Transfer) and GraphQL are two different approaches to building APIs, each with its own set of principles and use cases. Here's a comparison with sample examples to demonstrate how they work:

1. REST Architectural Pattern

Characteristics:

  • Resource-based: Everything in REST is considered a resource, which can be accessed through URIs (Uniform Resource Identifiers).
  • HTTP Methods: CRUD operations are mapped to HTTP methods (GET, POST, PUT, DELETE).
  • Multiple Endpoints: Typically, REST APIs have multiple endpoints for different resources.
  • Over-fetching/Under-fetching: Sometimes clients receive too much data or too little, needing extra requests.

Sample REST API Example

Let’s assume you have a service managing users and their posts.

Endpoint to Get Users

GET /users
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Response:

[
  {
    "id": 1,
    "name": "Alice",
    "age": 30
  },
  {
    "id": 2,
    "name": "Bob",
    "age": 25
  }
]
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Endpoint to Get Posts of a Specific User

GET /users/1/posts
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Response:

[
  {
    "postId": 101,
    "title": "REST vs GraphQL",
    "content": "Comparison between REST and GraphQL."
  },
  {
    "postId": 102,
    "title": "JavaScript Basics",
    "content": "Introduction to JavaScript."
  }
]
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Pros of REST:

  • Simplicity: Straightforward to design and understand.
  • Standardization: Uses HTTP methods (GET, POST, PUT, DELETE) consistently.
  • Caching: HTTP caching is well supported.

Cons of REST:

  • Over-fetching: If you only need the user’s name, you might get the entire user object, including data you don't need.
  • Multiple Requests: To get related data (e.g., posts of a user), multiple calls are often required.

2. GraphQL Architectural Pattern

Characteristics:

  • Single Endpoint: Typically, there is one single endpoint where all the queries and mutations are made.
  • Client-Specified Queries: The client defines the shape of the response, meaning you only fetch the data you need.
  • Efficient Data Fetching: Combines multiple resources into a single query.

Sample GraphQL API Example

GraphQL Query:

{
  users {
    id
    name
    posts {
      title
      content
    }
  }
}
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Response:

{
  "data": {
    "users": [
      {
        "id": 1,
        "name": "Alice",
        "posts": [
          {
            "title": "REST vs GraphQL",
            "content": "Comparison between REST and GraphQL."
          },
          {
            "title": "JavaScript Basics",
            "content": "Introduction to JavaScript."
          }
        ]
      },
      {
        "id": 2,
        "name": "Bob",
        "posts": []
      }
    ]
  }
}
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In this example, the client requested both users and their related posts in a single query, which avoids the need for multiple HTTP requests (as would be the case in REST).

Pros of GraphQL:

  • Avoids Over-fetching/Under-fetching: Only fetches the data requested by the client.
  • Single Request: Can fetch related data (e.g., users and posts) in a single request.
  • Flexible: The client decides exactly what data is needed, reducing bandwidth usage.

Cons of GraphQL:

  • Complexity: More complex to implement compared to REST.
  • Caching Issues: Since responses are custom, standard HTTP caching mechanisms don't work as well.
  • Learning Curve: Requires learning the GraphQL query language and tooling.

Key Differences at a Glance:

Feature REST GraphQL
Endpoint Structure Multiple endpoints (e.g., /users, /posts) Single endpoint (/graphql)
Data Fetching Fixed data structure in response Client specifies the data structure
Request Efficiency Multiple requests for related data Single request for nested data
Over/Under Fetching Can result in over/under-fetching Always fetches just what is needed
Learning Curve Lower Higher
Caching Well-supported via HTTP caching Requires custom caching solutions

Both patterns are powerful in their own right, and the choice between REST and GraphQL depends on the use case. REST is great for simple, resource-based services, while GraphQL is better for more complex services where data needs to be highly customized for the client.

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