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GraphQLRESTAPI DesignArchitecture

GraphQL vs REST: Choosing the Right API Architecture

A practical comparison of GraphQL and REST APIs, with guidance on when each approach shines and how AI can help implement either.

B
Bootspring Team
Engineering
January 29, 2026
6 min read

The GraphQL vs REST debate has raged for years. Both approaches have merit, and the right choice depends on your specific situation. Let's cut through the noise with practical guidance.

Understanding the Core Differences#

REST: Resource-Oriented#

REST models your API around resources with standard HTTP methods:

GET /users/123 → Get user POST /users → Create user PUT /users/123 → Update user DELETE /users/123 → Delete user GET /users/123/posts → Get user's posts

Philosophy: Server defines resources and representations. Client navigates through links.

GraphQL: Query-Oriented#

GraphQL models your API as a graph of types with a single endpoint:

1query { 2 user(id: "123") { 3 name 4 email 5 posts(first: 10) { 6 title 7 createdAt 8 } 9 } 10}

Philosophy: Client specifies exactly what data it needs. Server fulfills the request.

When REST Excels#

Simple CRUD Operations#

For straightforward resource manipulation, REST's conventions are elegant:

# REST API for a blog GET /posts # List posts POST /posts # Create post GET /posts/:id # Get post PUT /posts/:id # Update post DELETE /posts/:id # Delete post

AI can generate these quickly:

Create a REST API for managing products: - CRUD operations - Filter by category, price range - Pagination - Image upload Use Express with TypeScript.

Caching Requirements#

REST's URL-based resources work naturally with HTTP caching:

GET /products/123 Cache-Control: public, max-age=3600 GET /users/456 Cache-Control: private, max-age=300

CDNs, browsers, and proxies understand REST caching out of the box.

Public APIs#

REST's simplicity makes it accessible:

  • No special client libraries required
  • curl works great for testing
  • Wide tooling ecosystem
  • Easy to document with OpenAPI

File Operations#

Binary data handling is straightforward:

POST /files Content-Type: multipart/form-data GET /files/123/download Content-Type: application/octet-stream

When GraphQL Excels#

Complex Data Requirements#

When clients need data from multiple resources:

1# One query replaces multiple REST calls 2query DashboardData { 3 currentUser { 4 name 5 avatar 6 notifications(unread: true) { count } 7 } 8 recentOrders(first: 5) { 9 id 10 total 11 status 12 items { product { name } } 13 } 14 recommendations(first: 3) { 15 product { name, price, image } 16 reason 17 } 18}

REST would require multiple roundtrips:

  • GET /me
  • GET /me/notifications?unread=true
  • GET /me/orders?limit=5
  • GET /me/recommendations?limit=3

Mobile Applications#

Mobile apps benefit from GraphQL's flexibility:

  • Reduce bandwidth with precise field selection
  • Single request for complex screens
  • Adapt queries for different device capabilities

Rapidly Evolving Frontends#

GraphQL decouples frontend and backend evolution:

1# Frontend can add fields without backend changes 2query { 3 user { 4 name 5 email 6 # New field, already available if in schema 7 profileCompletion 8 } 9}

Multiple Client Types#

Different clients can request different data:

1# Mobile: minimal data 2query { user { name avatar } } 3 4# Desktop: rich data 5query { user { name avatar bio posts { title } } } 6 7# Admin: everything 8query { user { name avatar bio posts { title } audit { lastLogin } } }

Hybrid Approaches#

You don't have to choose one exclusively:

GraphQL for Reads, REST for Writes#

# Complex data fetching via GraphQL POST /graphql { "query": "{ user { ... } }" } # Simple writes via REST POST /api/users PUT /api/users/123 DELETE /api/users/123

GraphQL Gateway over REST Services#

┌─────────────────┐ │ GraphQL API │ │ (Gateway) │ └────────┬────────┘ │ ┌────┴────┬────────┬────────┐ ▼ ▼ ▼ ▼ ┌───────┐ ┌───────┐ ┌───────┐ ┌───────┐ │ Users │ │Orders │ │Products│ │Payments│ │ REST │ │ REST │ │ REST │ │ REST │ └───────┘ └───────┘ └───────┘ └───────┘

Implementation Considerations#

GraphQL Complexity#

GraphQL requires more infrastructure:

GraphQL needs: - Schema definition - Resolver implementation - N+1 query prevention (DataLoader) - Query complexity limiting - Depth limiting - Caching strategy - Authorization per field REST needs: - Route handlers - Standard HTTP caching - Standard authentication

AI can help manage GraphQL complexity:

Design a GraphQL schema for an e-commerce platform: Entities: User, Product, Order, Review, Category Requirements: - Efficient data loading (no N+1) - Field-level authorization - Pagination for lists - Filtering and sorting Include resolvers with DataLoader for batching.

REST Verbosity#

REST can become verbose for complex UIs:

1// Fetching dashboard data with REST 2const [user, orders, notifications, recommendations] = await Promise.all([ 3 fetch('/api/me'), 4 fetch('/api/me/orders?limit=5'), 5 fetch('/api/me/notifications?unread=true'), 6 fetch('/api/me/recommendations?limit=3'), 7]);

AI can help optimize REST APIs:

Design a REST API that minimizes roundtrips for this dashboard: Dashboard needs: - User profile - Recent orders with items - Unread notification count - Personalized recommendations Options to consider: - Compound endpoints - Sparse fieldsets - Includes/embeds Recommend approach with implementation.

Decision Framework#

Ask AI to help evaluate:

Help me choose between GraphQL and REST: Project: Social media mobile app Team: 4 developers (2 backend, 2 mobile) Timeline: 6 months to MVP Scale: Expected 100K users first year Features: - User profiles with posts, followers - News feed (complex aggregation) - Real-time messaging - Media uploads - Search Backend expertise: Strong REST, new to GraphQL Mobile expertise: Familiar with both Evaluate tradeoffs and recommend.

Performance Comparison#

REST Advantages#

  • Caching: HTTP caching is mature and understood
  • Simplicity: Less processing overhead
  • Predictability: Same endpoint, same work

GraphQL Advantages#

  • Efficiency: No over-fetching or under-fetching
  • Batching: Multiple resources in one request
  • Flexibility: Client-driven optimization

Real-World Considerations#

Analyze performance for these scenarios: Scenario 1: Product listing page - 20 products with minimal fields - REST: GET /products?fields=id,name,price,image - GraphQL: query { products { id name price image } } Scenario 2: Product detail page - Product + reviews + related + seller info - REST: 4 parallel requests - GraphQL: 1 request with nested query Which performs better in each case?

Migration Paths#

REST to GraphQL#

Plan incremental migration from REST to GraphQL: Current: 50 REST endpoints Traffic: 1M requests/day Team: Can dedicate 1 engineer Strategy: 1. Which endpoints to migrate first? 2. How to run both in parallel? 3. How to measure success? 4. Timeline estimates?

GraphQL to REST#

Less common, but sometimes necessary:

Our GraphQL API needs REST endpoints for: - Webhook integrations - Legacy client support - Public API simplicity Generate REST endpoints that wrap existing GraphQL resolvers.

Conclusion#

Neither GraphQL nor REST is universally better. The right choice depends on:

  • Data complexity: Complex, nested data favors GraphQL
  • Client diversity: Multiple clients with different needs favor GraphQL
  • Caching needs: Heavy caching favors REST
  • Team experience: Go with what you know for time-sensitive projects
  • Ecosystem: Consider what your tools support

Use AI to evaluate your specific situation rather than following trends. The best API is the one that serves your users effectively and your team can maintain successfully.

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