API

REST vs GraphQL

Compare REST and GraphQL API architectures - data fetching, flexibility, caching, tooling, and when to choose each approach.

REST vs GraphQL

Overview

REST (Representational State Transfer) is an architectural style using standard HTTP methods and resource-based URLs. GraphQL is a query language and runtime that lets clients request exactly the data they need from a single endpoint. Both are widely used for building APIs, but they take fundamentally different approaches to data fetching.

Feature Comparison

FeatureRESTGraphQL
ParadigmResource-basedQuery-based
EndpointsMultiple (per resource)Single endpoint
Data FetchingFixed structure per endpointClient specifies exact fields
Over-fetchingCommonEliminated
Under-fetchingCommon (requires multiple calls)Eliminated
HTTP MethodsGET, POST, PUT, PATCH, DELETEPOST (mostly)
CachingHTTP caching (built-in)Custom caching required
VersioningURL or header versioningSchema evolution (no versioning)
File UploadNative supportRequires workarounds
Real-timeWebhooks, SSE, WebSocketsSubscriptions (built-in)
Error HandlingHTTP status codes200 with errors array
DocumentationOpenAPI/SwaggerSelf-documenting (introspection)
ToolingMature, widespreadGrowing ecosystem
Learning CurveLowModerate
Type SystemOptional (OpenAPI)Built-in schema
BatchingNot built-inQuery batching native
N+1 ProblemManaged per endpointRequires DataLoader pattern

REST Pros & Cons

Pros:

  • Simple and well-understood
  • Leverages HTTP caching natively
  • Stateless by design
  • Wide tooling and library support
  • Easy to debug with browser/curl
  • Standard HTTP status codes for errors
  • File uploads are straightforward
  • Works well with CDNs

Cons:

  • Over-fetching and under-fetching issues
  • Multiple round trips for related data
  • API versioning complexity
  • Rigid response structures
  • Documentation requires extra tooling
  • Endpoint proliferation in complex APIs

GraphQL Pros & Cons

Pros:

  • Clients get exactly the data they need
  • Single endpoint simplifies architecture
  • Strongly typed schema acts as documentation
  • Introspection enables powerful tooling
  • Reduces number of API calls
  • Schema evolution without versioning
  • Great for complex, nested data

Cons:

  • HTTP caching is harder
  • Complexity in server implementation
  • N+1 query problem requires DataLoader
  • Security concerns (query depth, complexity)
  • File uploads need workarounds
  • Steeper learning curve
  • Overkill for simple APIs
  • All responses return 200 status

When to Use REST

  • Simple CRUD APIs with well-defined resources
  • Public APIs consumed by diverse clients
  • APIs that benefit heavily from HTTP caching
  • Microservices communication
  • File-heavy APIs (uploads/downloads)
  • Teams with limited GraphQL experience
  • APIs where simplicity and predictability matter
  • Integration with legacy systems

When to Use GraphQL

  • Applications with complex, interconnected data
  • Mobile apps needing bandwidth optimization
  • Frontends requiring flexible data queries
  • Rapid frontend iteration without backend changes
  • APIs serving multiple client types (web, mobile, IoT)
  • Dashboard and analytics applications
  • Projects where under-fetching is a major pain point
  • Backends consolidating multiple data sources (federation)

Verdict

Choose REST for simple, resource-oriented APIs where HTTP caching is important, your team values simplicity, or you are building public-facing APIs with diverse consumers.

Choose GraphQL when clients need flexible data fetching, your data is highly relational, or you want a strongly typed, self-documenting API that reduces round trips.

Many organizations use both: REST for simple services and public APIs, and GraphQL as a gateway to aggregate data from multiple backend services.