How to Handle Third-Party API Rate Limits Without Losing Data
Hitting a rate limit shouldn't mean losing data. Here's how we design integrations that queue, retry, and recover automatically instead of failing silently.
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Every few years a new API paradigm gets declared the future, and GraphQL had its moment. But the honest answer is that neither REST nor GraphQL is universally better — they solve different problems well.
REST is simple, cacheable, and every developer already understands it. If your API has predictable resources — users, orders, products — and clients generally need the full object, REST keeps things straightforward. HTTP caching, CDN support, and tooling are all mature and battle-tested.
GraphQL shines when clients have wildly different data needs — a mobile app that needs a lean payload versus a dashboard that needs deeply nested data. Instead of building five different REST endpoints or over-fetching data, a single GraphQL query lets each client ask for exactly what it needs.
GraphQL moves complexity from the client to the server. You need to think about query depth limits, N+1 query problems, and caching strategies that don't come for free like they do with REST. It's a real engineering investment, not just a syntax choice.
If you're building a straightforward CRUD-heavy application with a handful of client types, REST will get you there faster with less operational overhead. If you're supporting many different clients with very different data shapes — web, mobile, third-party integrations — GraphQL's flexibility starts paying for itself.
The wrong choice isn't picking REST or GraphQL — it's picking one because it's trendy instead of because it fits how your clients actually consume data.
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