data-performance-optimization

What problem does it solve?

Data-heavy applications often suffer from over-fetching, N+1 query patterns, and inefficient pagination, leading to slow responses and high resource usage.

Core Features & Use Cases

• Projections: enforce explicit field projections on MongoDB queries to minimize data transferred.
• Cursor-based pagination: replace skip() with cursor-based pagination, including complex cursors for non-unique sort fields, with index guidance.
• N+1 elimination: apply aggregation pipelines with $lookup or batched $in queries to minimize round-trips.
• Frontend data access: standardize data fetching via TanStack Query with explicit staleTime and correct invalidation strategies.
• Use Case: optimize a dashboard displaying thousands of records from MongoDB with minimal latency and predictable memory usage.

Quick Start

Replace all full-document fetches with explicit projections, switch pagination to cursor-based methods, and consolidate frontend data fetching with TanStack Query.