REST vs GraphQL on our platform: when to use each
Choosing the right API style shapes delivery speed, costs, and UX. For teams building an AI programming tool, an AI web design tool, or operating cloud app deployment pipelines, the trade-offs differ by workload, data shape, and operational risk.
Use REST when
- Resources map cleanly to nouns: /deployments, /models, /invoices.
- You need strong HTTP semantics: caching via ETag, 304s, Range, and clear idempotency on PUT/DELETE.
- CDN fan-out is critical (content, media, presets) and you want cache keys per URL.
- Compliance needs explicit versioning (v1/v2) and immutable contracts for partners.
- Incidents benefit from simple, grep-able logs and straightforward rate limiting.
Use GraphQL when
- Clients need tailored payloads (dashboards, editors) to avoid over/under-fetching.
- You orchestrate across many microservices and want a unified schema and fewer round-trips.
- You iterate UI rapidly: add fields without shipping new endpoints.
- Real-time patterns (subscriptions) power status boards or collaboration cursors.
Performance and caching
REST excels at edge caching: cache images, design tokens, and model manifests with long TTLs and hard versioned URLs. GraphQL benefits from persisted queries: ship hashed operations, enable CDN caching on the GET with the hash, and block ad-hoc queries in prod. For mobile, coalesce multiple view needs into one GraphQL query to cut TLS handshakes.
Security and governance
For REST, apply per-resource quotas, OAuth scopes, and HMAC for webhooks. For GraphQL, enforce depth/complexity limits, disable introspection in prod, require allowlisted persisted queries, and scope auth at field-level via directives. In both, standardize error codes and propagate correlation IDs.
Migration playbook
- Start with REST gateway; introduce a GraphQL BFF that composes existing endpoints.
- Adopt schema linting, breaking-change checks, and contract tests in CI.
- Measure success: p95 latency, bytes/response, and error budgets per operation.
- Map REST errors to GraphQL extensions; document retry and idempotency keys.
Case studies
- AI web design tool: REST serves rendered assets and templates through a CDN; GraphQL powers the editor's panel querying components, variants, and permissions in one call.
- AI programming tool: GraphQL aggregates suggestions, repo context, and feature flags; REST handles telemetry, model uploads, and billing webhooks with strict idempotency.
- Cloud app deployment: REST triggers deploys and rollbacks deterministically; GraphQL feeds a live dashboard of pod states, logs, and cost by environment.
Ops tips
- Instrument operations as first-class metrics; expose per-field resolvers in traces.
- Set sane timeouts; use dataloaders to batch N+1 in GraphQL.
- Version REST paths; deprecate GraphQL fields with sunset headers and schema hints.
- Cap list sizes, paginate consistently, and prefer cursors.
Decision checklist
- Edge cache needed and resources stable: choose REST.
- Client-specific views and rapid iteration: choose GraphQL.
- Hybrid wins often: REST for commands, GraphQL for reads.
Choose deliberately; align API style with product, platform, and teams.
