What Are REST and GraphQL? Compare Their Use Cases.

Concept

REST (Representational State Transfer) and GraphQL are two major architectural approaches for designing web APIs.
Both enable communication between clients (like web or mobile apps) and servers, but they differ fundamentally in data retrieval, endpoint structure, and flexibility.

REST uses multiple endpoints, each corresponding to a resource (e.g., /users, /orders).
GraphQL, created by Facebook (Meta), uses a single endpoint where the client specifies exactly what data it needs.

1. REST — Resource-Oriented Architecture

REST is a standardized approach based on HTTP methods and URIs to represent resources.

Key Principles:

Resources: Each entity (user, post, product) has its own endpoint.
Statelessness: Every request contains all necessary context; no session state is stored on the server.
HTTP Verbs: GET, POST, PUT, PATCH, and DELETE map to CRUD operations.
Caching: Native HTTP caching headers (ETag, Cache-Control) improve performance.
Versioning: Typically managed via URLs (/v1/users) or headers.

Example (safe for MDX):

GET /api/users/42
Response:
{
  "id": 42,
  "name": "Alice",
  "email": "alice@example.com",
  "orders": [ ... ]   # fixed data structure
}

Advantages:

Simple and widely understood.
Mature ecosystem and tooling.
Naturally fits RESTful HTTP conventions.
Excellent caching support.

Drawbacks:

Over-fetching: Returns more data than needed.
Under-fetching: May require multiple requests to get related data.
Requires versioning for backward compatibility.

2. GraphQL — Query-Based API Paradigm

GraphQL is a flexible query language and runtime for APIs. Instead of calling multiple endpoints, the client sends a single query to a single endpoint, specifying exactly what data it needs.

Example (safe for MDX):

POST /graphql
{
  user(id: 42) {
    name
    email
    orders {
      total
      date
    }
  }
}

Response:

{
  "user": {
    "name": "Alice",
    "email": "alice@example.com",
    "orders": [{ "total": 99.99, "date": "2025-10-01" }]
  }
}

Advantages:

Exact data retrieval: Avoids over- and under-fetching.
Single endpoint: Simplifies client configuration.
Strong typing: The schema defines all available queries, types, and relationships.
Real-time updates: Supports subscriptions for live data (e.g., chats, notifications).
Schema evolution: Changes can be made without breaking clients.

Drawbacks:

Requires custom caching and error handling.
More complex server setup and query optimization.
Can be overkill for simple, static APIs.
Performance risks if clients request overly nested or large queries.

3. Core Comparison

Feature	REST	GraphQL
Endpoint Structure	Multiple endpoints (`/users`, `/posts`)	Single endpoint (`/graphql`)
Data Fetching	Over- or under-fetching possible	Precise data retrieval
Versioning	New endpoints for changes (e.g., `/v2/users`)	Schema evolution, no versioning
Caching	Built-in HTTP caching	Custom caching (Apollo, Relay)
Batching Requests	Multiple calls	Single query for multiple resources
Error Handling	HTTP status codes	Partially successful responses with `errors` field
Learning Curve	Easier for beginners	Requires schema and resolver knowledge

4. When to Use REST

When simplicity and speed of setup matter (e.g., MVPs, CRUD APIs).
When caching and HTTP semantics are beneficial.
For APIs with predictable, uniform data structures.
When you need to expose public APIs with well-known standards.

Example Use Cases:

Payment gateways (Stripe API).
Authentication systems.
Traditional backend services.

5. When to Use GraphQL

When clients (e.g., mobile, web, IoT) have different data requirements.
When reducing network calls is critical (low bandwidth or mobile-first environments).
For complex, relational data models (nested or interlinked resources).
When you need real-time updates (GraphQL subscriptions).

Example Use Cases:

Shopify and GitHub APIs use GraphQL for flexible client queries.
Facebook/Instagram: Handles diverse data needs across many platforms.
E-commerce dashboards: Custom queries for analytics and product listings.

6. Performance and Scalability Considerations

REST’s fixed responses are easier to cache and monitor using CDNs.
GraphQL’s dynamic queries make caching harder but reduce total requests.
REST is better for simple, high-volume endpoints.
GraphQL excels for aggregated, client-specific data or microservice orchestration.

7. Example Analogy

Analogy	REST	GraphQL
Restaurant Menu	You order a fixed meal from the menu.	You specify exactly which ingredients you want.
Data Retrieval	Multiple trips to get different dishes.	One trip with a custom order.

8. Hybrid Approach

Many modern APIs use both:

REST for public, stable endpoints.
GraphQL for internal dashboards, microservices, or mobile apps needing flexibility. This hybrid model provides predictability for consumers and agility for internal teams.

Interview Tip

Clarify that GraphQL is not a replacement but an alternative paradigm.
Discuss trade-offs: REST’s maturity vs GraphQL’s adaptability.
Mention tooling ecosystems — Postman and Swagger (REST) vs Apollo and GraphiQL (GraphQL).
For design interviews, emphasize choosing based on data shape, client diversity, and caching needs.

Summary Insight

REST is resource-driven and ideal for stable, predictable APIs. GraphQL is client-driven and excels at flexible, efficient data fetching. Choose REST for simplicity and scalability; choose GraphQL for customization and evolving client needs.