API Design Principles: REST, GraphQL, and When to Use Which

We've built over 80 APIs across REST, GraphQL, and a handful of gRPC services. The 'REST vs GraphQL' debate generates more heat than light because the answer always depends on context - your team's expertise, your data model's complexity, your client diversity, and your scale requirements. Here's how we actually make the decision.

REST is our default, and here's why. REST APIs are universally understood. Every developer on every platform knows how to call a REST endpoint. Every HTTP client, every monitoring tool, every CDN, every API gateway works with REST out of the box. HTTP caching works natively - a GET request with proper cache headers costs zero server resources on subsequent calls. This matters at scale: we've seen REST APIs handle 50,000 requests per second with aggressive caching that would require custom solutions in GraphQL.

When REST becomes painful. REST's resource-oriented model breaks down when your frontend needs data from multiple resources in a single view. A dashboard that shows user profile, recent orders, account balance, notification count, and team activity requires 5 separate API calls in REST - or a custom endpoint that couples backend to frontend layout. Neither is great. REST also struggles with deeply nested relationships: fetching a project with its team members, their roles, their recent activity, and their notification preferences becomes either N+1 queries or complex include/sideloading logic.

GraphQL's real strength: flexible data fetching. GraphQL lets the frontend request exactly the data it needs in a single round trip. That dashboard? One query. The nested project view? One query. A mobile app that needs less data than the web app? Same API, different query. This flexibility is genuinely powerful when you have diverse clients (web, mobile, partner APIs) consuming the same data in different shapes. The reduction in round trips and payload size is measurable and significant.

GraphQL's real cost: complexity. GraphQL adds layers that REST doesn't require: a schema definition language, a resolver architecture, query complexity analysis (to prevent resource-exhausting queries), authorization at the field level (not just the endpoint level), and caching strategies that don't map to HTTP standards. Your team needs to learn these patterns, your monitoring needs to understand GraphQL-specific metrics, and your API gateway needs GraphQL-aware features. For a team of 3 engineers building a standard CRUD application, this overhead is rarely justified.

Our decision matrix in practice. We score five factors: client diversity (multiple frontends with different data needs favor GraphQL), data relationship complexity (deeply nested models favor GraphQL), caching requirements (heavy read loads favor REST), team expertise (REST knowledge is nearly universal; GraphQL expertise is less common), and real-time requirements (both handle subscriptions, but GraphQL subscriptions are more elegant). Score under 12: REST. Score 12-18: REST with a few aggregation endpoints. Score above 18: GraphQL deserves serious consideration.

API design principles that apply regardless of paradigm. Whether you choose REST or GraphQL, these principles make your API professional: consistent naming conventions (plural nouns for resources, verb prefixes for actions), comprehensive error responses (machine-readable code, human-readable message, documentation link), pagination on every list endpoint (cursor-based for real-time data, offset for static data), rate limiting with clear headers (X-RateLimit-Remaining, Retry-After), and idempotency keys for all write operations (so retries don't create duplicates).

Versioning strategy: plan for change from day one. APIs evolve. Fields get deprecated. New resources get added. Response shapes change. Our approach: URL-based versioning for REST (/v1/users, /v2/users) because it's explicit, cacheable, and easy to monitor separately. For GraphQL: schema evolution with @deprecated directives and a deprecation timeline that gives clients 6 months to migrate. Never break a published API contract without a versioned alternative available first.

Authentication and authorization patterns. JWT tokens for stateless authentication across both REST and GraphQL. API keys for machine-to-machine communication. OAuth 2.0 for third-party integrations. The key difference: REST authorization happens at the route/middleware level (easy to reason about - if you can access /admin, you can access everything under /admin). GraphQL authorization happens at the resolver or field level (more granular but more complex - you need to think about every field's visibility independently).

Documentation is your API's user experience. We treat API documentation as a product interface, not an afterthought. Every endpoint has: a description of what it does and when to use it, request/response examples with realistic data, error response examples with remediation guidance, rate limit information, and changelog entries for recent changes. For REST, we use OpenAPI/Swagger with auto-generated interactive documentation. For GraphQL, the schema is self-documenting, supplemented with description fields and a dedicated guide for common query patterns.