- cc: stefantmd jensneuse_de graphql trpc
explained this diagram in depth and at first glance, it makes a lot of sense. tRPC doesn't require a compile-time step, the developer experience is incredible, and it's a lot simpler than GraphQL.
If we were to use tRPC, we would create a "procedure" to load all this data in one go. We'd call this procedure at the top of the page and then propagate the data down to the components.import { trpc } from '../utils/trpc' export function NewsFeed { const feed=trpc.newsFeed.useQuery return }export function NewsFeedList { return => )} {feed.
Keep in mind that this is just one single page. What happens if we add similar but slightly different pages? Does this approach scale well if we're adding more and more pages? Does this not sound like the problem we've had with REST APIs? We've even got famous names for these problems, like Overfetching and Underfetching, and we haven't even gotten to the point where we're talking about the N+1 problem.
Let's look at the same example using GraphQL, Fragments, and Relay. For laziness reasons, the code is not 100% correct because I'm using Copilot to write it, but it should be very close to what it would look like in a real app.Next, let's look at the feed list component. The feed list component declares a fragment for itself, and includes the fragment for the feed item component.
It's important to understand that this is a trade-off. There's no free lunch. The simplicity of tRPC comes at the cost of flexibility. Both REST and GraphQL are built with collaboration in mind. Not all teams will be using TypeScript, and if you're crossing company boundaries, you'll want to expose APIs in a way that's easy to understand and consume.
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