GraphQL Clients (Apollo)
You can write a GraphQL query in five minutes. Then you wire it into a real app and the questions start: where does the response live, why does one component update when another runs a mutation, and how do you stop the same data being fetched four times? A raw fetch won't answer any of that. Apollo Client does, and this guide is about the model that makes it work.
The relief here is that once you understand Apollo's normalized cache, most of the busywork of front-end data fetching disappears. You stop hand-managing loading flags, stale lists, and duplicated requests, because the cache does it for you. The cost is a new mental model you have to actually hold in your head, and a few new ways to get burned.
How to read this
Read the phases in order. Phase 1 builds the mental model: what Apollo Client is, why a cache sits at its center, and how that differs from thinking in REST endpoints. Phase 2 is the everyday work: writing queries and mutations with hooks, and keeping the cache honest after a write. Phase 3 is production reality: the gotchas that bite, from cache misses to refetch storms.
If you've never written a GraphQL query at all, skim GraphQL Explained first, then come back. If REST is your only reference point, REST APIs Explained gives you the contrast this guide keeps drawing on.
The phases
- The cache is the point - what Apollo Client actually is, and why a normalized cache changes everything
- Queries and mutations in real components - the hooks you use daily, and updating the cache after a write
- When the cache lies to you - cache misses, refetch storms, and the tradeoffs you signed up for