GraphQL is a popular alternative to REST for APIs, and its interviews test why it exists (precise data fetching), how the schema and resolvers work, and the trade-offs versus REST. Here are the GraphQL interview questions that actually get asked, with answers. (See also our REST API guide.)
Fundamentals
- What is GraphQL, and what problem does it solve?
- GraphQL vs REST — over-fetching and under-fetching.
- Queries vs mutations vs subscriptions.
- What is the schema and the type system (SDL)?
- Single endpoint — why?
Resolvers & execution
- What is a resolver and how does it work?
- The resolver chain; how nested queries resolve.
- Arguments and variables.
- Fragments.
Performance & practical concerns
- The N+1 problem in GraphQL and how DataLoader solves it.
- Caching challenges compared to REST.
- Error handling and partial responses.
- Security — query depth limiting, rate limiting.
How to prepare
GraphQL rounds probe the model and trade-offs versus REST. Practise explaining resolvers and the N+1 fix out loud. Greenroom runs spoken technical interviews that follow up on your reasoning. Pair it with our REST API and backend guides.
Frequently asked questions
What are the most common GraphQL interview questions?
Common GraphQL questions cover what GraphQL is and the problems it solves, GraphQL vs REST (over-fetching and under-fetching), queries vs mutations vs subscriptions, the schema and type system, the single endpoint, resolvers and the resolver chain, arguments, variables and fragments, the N+1 problem and DataLoader, caching challenges, error handling, and security like query depth limiting.
What is the difference between GraphQL and REST?
REST exposes multiple endpoints that each return fixed data structures, which can cause over-fetching (getting more than you need) or under-fetching (needing multiple requests). GraphQL exposes a single endpoint where the client specifies exactly which fields it wants in one query, eliminating over- and under-fetching. The trade-off is that GraphQL complicates HTTP caching and can introduce N+1 query problems.
What is the N+1 problem in GraphQL?
The N+1 problem occurs when resolving a list field triggers one query for the list and then a separate query for each item's nested data, resulting in N+1 database calls. It's solved with batching and caching via a tool like DataLoader, which collects the individual requests within a tick and resolves them in a single batched query, dramatically reducing database round trips.
How should I prepare for a GraphQL interview?
Focus on the schema and resolver model, the trade-offs versus REST (precise fetching vs harder caching), and performance concerns like the N+1 problem and DataLoader. Practise explaining how resolvers work and when GraphQL beats REST out loud with a voice-based mock interview that follows up, since these rounds probe understanding and trade-offs rather than syntax.