Why is my Cloud Firestore query slow?
Blog post from Firebase
Cloud Firestore queries generally scale with result-set size, but perceived slowness can arise from transferring large documents or many results, searching an oversized local offline cache, inefficient zig-zag merge joins across fields with little overlap, differences in latency compared with Firebase Realtime Database, or unavoidable network distance between users and database regions. Recommended mitigations include limiting and paginating queries, separating frequently needed fields from larger details, keeping documents and cached collections smaller, avoiding unnecessary cache preloading, adjusting or testing offline persistence settings, and creating composite indexes for slow multi-field queries. Applications requiring exceptionally low latency, particularly in North America, may benefit from using Realtime Database for suitable features, while realtime listeners can improve responsiveness through cached data and local write visibility. Developers should choose a Firestore region near most users and use Firebase Performance Monitoring with custom traces to measure behavior under real-world conditions.
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