tanstack-query-best-practices

TanStack Query caching uses consistent query key arrays to enable dependency tracking and targeted invalidation. Organizing keys hierarchically ensures predictable cache management and safe, testable mutation patterns across React components.

Handling mutations with optimistic updates involves applying proven patterns to update the UI immediately while managing server state rollback on error boundaries. This approach reduces boilerplate and ensures robust data handling during failed requests.

SSR hydration patterns for TanStack Query involve dehydrating server state and rehydrating it on the client to prevent fetch waterfalls. Applying these structured patterns ensures reliable server-state initialization and scalable organization for large React apps.

Targeted query invalidation should be used when you need to selectively refresh specific cached server state after mutations, rather than triggering broad refetches. This precise invalidation strategy prevents redundant network requests and maintains data consistency across components.

TanStack Query best practices are designed for large-scale React applications, providing scalable organization for server state. The catalog of rules ensures consistent query keys, robust caching strategies, and testable data-fetching patterns across complex component hierarchies.