MongoDB Advanced Techniques: Going Beyond the Basics

This post covers the MongoDB patterns and strategies I reach for most often when building applications that need to handle real traffic. Aggregation pipelines, schema design patterns with working examples, index strategies that survive production, and the operational features that tie it all together. What's covered: The Aggregation Pipeline Schema Design Patterns - Bucket, Computed, Outlier Time-Series Collections Index Strategies - ESR rule, partial indexes, wildcard indexes Change Streams Transactions - write concerns, retryable writes, session handling Query Performance The Aggregation Pipeline: Your Most Powerful Tool The aggregation pipeline is where MongoDB truly shines. Think of it as a series of stages that your data flows through, each one transforming it along the way. While most developers know $match and $group , the real power comes from combining lesser-known stages. $facet lets you run multiple aggregation pipelines in parallel on the same set of input documents. This i