REST vs GraphQL on Your Platform: Make the Right Call
Both APIs are first-class on the platform, but they solve different problems. Think in terms of data shape, team topology, and runtime constraints. Below is a practical rubric we use with enterprise teams building AI features, dashboards, and high-traffic services.
When REST wins
- Stable resources, predictable flows: orders, invoices, devices. Version endpoints cleanly without breaking clients.
- Edge caching: CDN and gateway caches thrive on idempotent GETs. Perfect for product catalogs and public profiles.
- Compliance and observability: per-endpoint rate limits, audit trails, and WAF rules are simpler.
- Streaming and webhooks: native SSE, chunked uploads, and signed callbacks fit REST patterns.
Example: A B2B billing service cut latency 32% by caching GET /prices at the edge-no schema coordination required.
When GraphQL wins
- Client-driven UIs: an AI web design tool can query exactly the fields it renders, shrinking overfetch by 40-70%.
- Aggregations across domains: stitch users, usage, and spend in a single roundtrip for executive dashboards.
- Schema as contract: types unlock codegen for mobile, web, and your AI programming tool's integration tests.
- Evolving surfaces: add fields without bumping versions; deprecate gracefully.
Case study: A learning platform replaced five REST calls with one GraphQL query and saved 280 ms p95 in global regions.
Hybrid patterns on the platform
- Expose REST for hot, cacheable reads; mount a GraphQL gateway for composed views.
- Back GraphQL resolvers with internal REST or gRPC; keep ownership localized to microservices.
- Publish a typed event stream; let GraphQL subscribe for realtime dashboards.
Operational playbook
- Cost: In GraphQL, protect backends with query cost analysis and depth limits; in REST, enforce per-route quotas.
- Caching: REST-CDN + ETags. GraphQL-response caching on persisted queries; ban ad-hoc query text in production.
- Pagination: REST-RFC 5988 links. GraphQL-cursor connections; never offset on large tables.
- Errors: Map domain errors to typed unions in GraphQL; use problem+json in REST.
Security and governance
- Auth: OAuth2/JWT for both. In GraphQL, authorize at field or resolver level.
- PII boundaries: hide sensitive joins behind dedicated resolvers or separate REST domains.
- Schema discipline: adopt ADRs; require review for breaking changes; automate SDL diff checks in CI.
Cloud app deployment tips
- Deploy GraphQL behind a managed gateway with persisted operations and CDN.
- Pin REST versions in ingress; roll forward with canaries and synthetic checks.
- Auto-generate clients from OpenAPI/SDL so your AI programming tool can scaffold tests.
Decision rule: prefer REST for cacheable resources and clear boundaries; choose GraphQL for cross-domain views, fast-evolving UIs, and AI-driven experiences.
Quick heuristic: if caching and compliance dominate, ship REST first; if front-end teams iterate weekly, start GraphQL. For mixed estates, layer both: REST for resources, GraphQL for views, and measure p95 latency, error budgets, and cloud cost before standardizing globally.
