Comparison
REST vs GraphQL: Choosing Your API Architecture
Resource-oriented endpoints versus flexible queries. Both have earned their place.
REST and GraphQL are the two dominant API paradigms for web and mobile applications. REST uses resource-based URLs and HTTP methods, while GraphQL provides a single endpoint with a typed query language that lets clients request exactly the data they need.
Overview
The Full Picture
REST (Representational State Transfer) has been the dominant API paradigm since the mid-2000s. It maps CRUD operations to HTTP methods (GET, POST, PUT, DELETE) on resource URLs, and it leverages HTTP caching, status codes, and content negotiation natively. REST APIs are simple to understand, easy to cache, and well-supported by every programming language and HTTP client. OpenAPI (Swagger) provides a standardized specification format that enables automatic documentation, client generation, and validation. For most CRUD-oriented applications, REST is straightforward and effective.
GraphQL, developed by Meta and released publicly in 2015, takes a fundamentally different approach. Instead of multiple endpoints, GraphQL exposes a single endpoint with a typed schema that describes all available data and operations. Clients write queries specifying exactly which fields they need, solving the over-fetching and under-fetching problems common in REST APIs. A single GraphQL query can retrieve related data that would require multiple REST calls, reducing network round trips. The type system enables excellent developer tooling, including autocomplete, validation, and automatic documentation. However, GraphQL introduces complexity in areas where REST is simple: HTTP caching does not work natively (all requests are POST to one URL), query complexity can lead to performance issues if not managed, and the learning curve for server implementation is steeper.
Adapter's API practice has implemented both paradigms at scale. We default to REST for most server-to-server communication, simple CRUD APIs, and public APIs where caching and simplicity are priorities. We recommend GraphQL when the client has complex, nested data requirements (common in mobile apps with limited bandwidth), when multiple frontend teams consume the same API with different data needs, or when the API powers a rich, interactive UI that benefits from GraphQL's subscription model for real-time updates. We also see strong results from tRPC for TypeScript-to-TypeScript communication, which provides end-to-end type safety without schema definition overhead. The pragmatic approach is often to use REST for external APIs and either GraphQL or tRPC for internal frontend-to-backend communication, depending on the team's TypeScript adoption and data complexity.
At a glance
Comparison Table
| Criteria | REST | GraphQL |
|---|---|---|
| Data fetching | Fixed per endpoint | Client-specified |
| HTTP caching | Native | Manual |
| Learning curve | Low | Moderate |
| Tooling | Universal | Specialized |
| Real-time support | SSE / WebSocket | Built-in subscriptions |
| Type safety | Via OpenAPI | Built-in schema |
Option A
REST
Best for: Public APIs, simple CRUD applications, server-to-server communication, and scenarios where HTTP caching is important.
Pros
Simplicity
HTTP methods on resource URLs are intuitive and well-understood by virtually every developer.
Native HTTP caching
GET requests are cacheable by default at every layer (browser, CDN, proxy), significantly reducing server load.
Universal tooling
Every language, framework, and HTTP client supports REST. OpenAPI provides standardized specs.
Stateless by design
Each request is self-contained, making REST APIs easy to scale horizontally and load-balance.
Cons
Over-fetching
Endpoints return fixed data shapes, often including fields the client does not need.
Under-fetching
Complex data requirements may require multiple sequential requests, increasing latency.
Versioning complexity
API changes often require versioning (v1, v2) which creates maintenance overhead.
Option B
GraphQL
Best for: Mobile apps with bandwidth constraints, complex nested data requirements, and scenarios where multiple clients need different data shapes.
Pros
Precise data fetching
Clients request exactly the fields they need, eliminating over-fetching and reducing payload sizes.
Single request for complex data
Nested queries retrieve related data in one round trip instead of multiple sequential REST calls.
Typed schema
Self-documenting API with introspection, enabling powerful developer tools and automatic client generation.
Real-time subscriptions
Built-in subscription model for real-time data updates via WebSocket.
Cons
Caching complexity
HTTP-level caching does not work natively. Requires client-side cache solutions like Apollo or urql.
Query complexity risks
Unrestricted queries can be expensive. Requires depth limiting, complexity analysis, or persisted queries.
Steeper server implementation
Schema definition, resolvers, and N+1 query prevention (DataLoader) add implementation overhead.
Larger learning curve
Teams need to learn schema design, resolver patterns, and cache management beyond basic HTTP knowledge.
Side by Side
Full Comparison
| Criteria | REST | GraphQL |
|---|---|---|
| Data fetching | Fixed per endpoint | Client-specified |
| HTTP caching | Native | Manual |
| Learning curve | Low | Moderate |
| Tooling | Universal | Specialized |
| Real-time support | SSE / WebSocket | Built-in subscriptions |
| Type safety | Via OpenAPI | Built-in schema |
Verdict
Our Recommendation
REST remains the best default for most APIs due to its simplicity, caching, and universal support. GraphQL is the right choice when data complexity, multiple client types, or bandwidth constraints make precise data fetching valuable. Adapter often uses REST for external APIs and GraphQL or tRPC for internal frontend communication.
FAQ
Common questions
Things people typically ask when comparing REST and GraphQL.
Need help choosing?
Adapter helps teams make the right technology and strategy decisions. Tell us about your project and we will point you in the right direction.