What are the performance optimization techniques for Firestore queries?

Firestore query performance optimization: (1) Index optimization — ensure composite indexes exist for all multi-field queries. Missing indexes cause queries to fail; extra indexes slow writes and increase storage costs. Audit indexes regularly; (2) Limit data fetched — use limit() to fetch only needed documents; use select() (field masks) to fetch only needed fields: query(collection(db, "users"), select("name", "email"), limit(20)); (3) Avoid large document reads — don't store large binary data or huge arrays in documents; use Cloud Storage for files; (4) Aggregate queries — use getCountFromServer() and getAggregateFromServer() instead of fetching all documents to count: cheaper and faster; (5) Client-side caching — cache frequently accessed, rarely changing data (user profiles, settings) in memory or localStorage; (6) Reduce listener count — each active listener consumes resources; merge multiple document listeners into one collection query where possible; (7) Pagination — never fetch unbounded collections; always paginate with limit(); (8) Composite index order — equality fields first, then range/order fields in composite indexes; (9) Colocation — use the nearest Firestore region to reduce latency.