Hire GraphQL Developers Who Design The Schema Before The Endpoints

Not universally, and anyone who says so is selling something. GraphQL earns its place when many different clients need different shapes of the same data, when mobile bandwidth makes over-fetching expensive, or when a screen currently needs four REST calls to render. A small API with one client and stable endpoints is usually simpler in REST, and staying there is a legitimate answer.

Clients ask for exactly the fields they need, in one request, across related resources. That removes both over-fetching, where a response carries data nobody uses, and under-fetching, where a screen has to make several calls in sequence. The trade is that the server no longer controls the shape of what it is asked for, which is why the operational concerns shift.

A query asks for a list of items and a field on each one, so the resolver runs one query for the list and then one more per item. Twenty items become twenty-one database calls, and nested fields multiply it further. The fix is batching through a data loader, which collects the individual lookups within a request and resolves them together. It comes up constantly because it is invisible until the list gets long.

REST gets HTTP caching almost free, because a URL identifies a resource and a cache can key on it. GraphQL usually posts to a single endpoint with a different query each time, so there is nothing obvious to key on. The workable answers are persisted queries, caching at the entity level rather than the response level, and edge caching for the queries that repeat. It is solvable, it just has to be designed in.

Without limits in place, deeply nested queries can be expensive enough to cause real problems. That is why a production graph needs depth and complexity limits, timeouts, and rate limiting based on the cost of a query rather than the number of requests. Introspection is also worth controlling by environment. None of this is exotic, but it is not on by default.

Incrementally. The graph starts by wrapping existing REST services, so it is a new way to ask for the same data rather than a rewrite. Clients move endpoint by endpoint on their own schedule, and resolvers are replaced with direct data access where the wrapping becomes the bottleneck. Both APIs run together for as long as that takes, which is usually longer than anyone plans for.

No, and this is the most common early mistake. A schema generated from tables exposes your storage decisions to every client, which means changing the database becomes a breaking API change. The schema should describe your domain in the language your product uses. Storage sits behind the resolvers where it can change freely.

Only when several teams need to own parts of one graph independently. Federation solves an organisational problem more than a technical one, and it brings real operational overhead: a gateway, composition checks and coordinated schema changes. One team with one service almost never needs it, and adopting it early tends to cost more than it returns.

Less often than people expect. Subscriptions hold open connections and add infrastructure to manage, so they are worth it when updates must arrive within seconds and matter to the user, such as live collaboration or order status. For a dashboard that refreshes every thirty seconds, polling is simpler, cheaper and easier to reason about when something goes wrong.