graphql-design

Prevent N+1 query issues in GraphQL resolvers by integrating DataLoader for per-request batching and caching. This pattern groups multiple individual data fetch requests into a single batched query, optimizing data fetching and ensuring scalable backend performance.

Structure GraphQL schemas for maintainability using modular type definitions and clear input/output contracts. This approach separates concerns across domains, reducing boilerplate and preventing common structural pitfalls as the production API scales.

Implement Relay-style pagination in a GraphQL API by enforcing cursor-based connections within your schema design. This standardizes how clients request large datasets, ensuring scalable data fetching and consistent query structures for real-time applications.

Handle GraphQL mutation errors and results using typed mutation payloads that return both the operation results and actionable errors. This structured approach provides clear output contracts, streamlining client-side error handling and data processing.

Yes, you can add real-time subscriptions to a scalable GraphQL backend. The design includes subscription support alongside modular type definitions, enabling live data updates while maintaining robust schema structure and preventing data fetching bottlenecks.