4 posts tagged with "Performance"

Here's a sentence that should terrify anyone running a GraphQL API in production: "Our iOS app sends arbitrary query strings to our server, and we just trust them." You wouldn't let your web app send raw SQL. You wouldn't let a mobile client dictate the shape of a REST response. Yet for some reason, we've collectively decided it's fine to let clients write GraphQL queries of any depth, width, and cost, and we'll just sort it out at runtime with complexity analysis and rate limits. Persisted documents are how mature GraphQL teams fix this, and in 2026 there's finally enough consensus to do it properly.

For a decade, GraphQL responses came back as one lump. You asked for a page, you waited for every field to resolve, then the server wrapped it up and sent it over the wire in one envelope. Fast fields waited for slow fields. The whole response moved at the speed of its slowest resolver. Then @defer and @stream arrived to fix exactly that. They've been maturing as a proposal for several years - deliberately, because getting incremental delivery right is genuinely hard - and they're now real enough to use with modern clients and servers. The open question is when they pay off, and both camps have a case.

"Just add caching" they said. "It'll be easy" they said. Three weeks later, I emerged from my cave with bloodshot eyes and a newfound respect for cache invalidation. This is my story.

The N+1 problem can turn your elegant GraphQL API into a database nightmare. Learn how Spring GraphQL's batch loading solves this efficiently.