Mongodb Schema Design

MongoDB performance problems usually trace back to schema design, not queries or indexes. This skill helps you decide between embedding and referencing data, avoid common anti-patterns like unnecessary collections and excessive lookups, and apply proven patterns like bucketing for time series or the extended reference pattern for caching frequently accessed fields. It's especially useful when migrating from SQL where the instinct to normalize everything will hurt you, or when you're hitting the 16MB document limit from unbounded arrays. The core principle is simple: data accessed together should be stored together. If you're doing a lot of lookups or your queries span multiple collections, your schema probably needs rethinking.