REST vs GraphQL on our low-code AI platform: when to pick each
Building enterprise apps on a low-code AI platform—or evaluating a Webflow app builder alternative—often comes down to API strategy. Here’s a pragmatic guide drawn from our software engineering services for AI apps, covering how REST and GraphQL behave on the same platform and where each wins.
Platform wiring: how requests flow
On our stack, REST routes map to versioned microservices with edge caching; GraphQL resolves via a federated gateway with persisted queries and per-field tracing. Observability and budgets are set per tenant.
Choose REST when
- Commands dominate: create job, start training run, cancel invoice. Clear resource ownership and idempotency matter.
- You need CDN/ETag caching, range requests, or large uploads/webhooks.
- Strict SLAs with predictable latency and simpler failure modes are required.
- Auditability via HTTP semantics (verbs, status codes) is a compliance need.
Choose GraphQL when
- Clients must shape data for complex UIs (dashboards, chat agent timelines) in one round trip.
- Mobile networks or LLM tools need sparse, nested fields without over-fetching.
- You ship UI fast on a low-code AI platform and want schema-driven scaffolding.
- You plan feature flags and A/B tests by adding fields without new endpoints.
Patterns that scale
- REST: use PATCH for partial updates; prefer cursor pagination; expose idempotency keys on POST.
- GraphQL: enable persisted queries, cost limits, depth/alias guards; use @defer/@stream for long lists.
- Shared: contract tests at CI, golden traces in staging, and SLOs per operation.
Anti-patterns
- GraphQL mutations that hide transactional side effects without events.
- REST endpoints that leak view models (report-specific shapes) instead of resources.
- Exposing unbounded filtering server-side without indexes or query complexity caps.
Decision rubric by feature
- File uploads, webhooks, billing callbacks: REST.
- Analytics boards, admin consoles, partner portals: GraphQL.
- Chatbot session state: REST for commands, GraphQL for transcript reads.
- Search: REST for simple query, GraphQL when aggregations and facets are dynamic.
Performance playbook
- REST: ETags, 304s, gzip/br, retry with backoff, HATEOAS for discoverability.
- GraphQL: dataloader batching, field-level caching, persisted operations at the edge.
Security and governance
Adopt OAuth2 or mTLS; enforce row-level access in resolvers; sign webhooks; log query signatures; and maintain a deprecation calendar. For regulated tenants, publish a REST change log and a GraphQL schema diff feed.
Migration checklist
- Inventory endpoints and graph types; tag by read/write and latency SLOs.
- Add a gateway with persisted queries; stand up REST adapters for webhooks.
- Ship one pilot feature, measure p95, error rate percentage, and cache hit ratio baseline.
Bottom line: mix both. Use REST for commands and integration surfaces, GraphQL for read-heavy UIs. This blend lets an enterprise treat the platform as a true Webflow app builder alternative while our software engineering services for AI apps harden it for scale.
