MongoDB Indexes Explained: B-Trees, ESR Rule, and Query Optimization Tips

A technical guide published on DEV Community revisits how MongoDB uses B-Tree data structures to power collection indexes, enabling logarithmic O(log N) query lookups instead of full document scans. Every MongoDB collection automatically receives a unique index on the _id field, while additional indexes must be designed carefully using the Equality-Sort-Range (ESR) rule to avoid inefficient in-memory sorting. Developers are advised to run explain('executionStats') to detect slow COLLSCAN operations and monitor the ratio of documents examined versus documents returned. The guide also covers compound, multikey, text, and TTL index types, mapping each to specific query patterns. A key trade-off highlighted is that indexes consume memory and slow down write operations, so write-heavy workloads such as IoT telemetry should use as few indexes as possible.