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A comprehensive guide to MongoDB schema design and aggregation patterns for developers transitioning from relational databases. Covers the core mental shift of modeling around access patterns rather than normalization, three structural patterns (Attribute, Bucket, Computed), the embed vs. reference decision with a practical checklist, and the Subset/Hybrid pattern. The aggregation pipeline section walks through $match, $group, $lookup, $unwind, $project, $addFields, and $facet with real-world scenarios including a monthly revenue cohort analysis. Also addresses performance considerations like using explain(), compound indexes, avoiding $where, and common pitfalls like unbounded embedded arrays and overusing $lookup in hot paths.

Document Database Design Patterns: MongoDB Best Practices for Scalable Applications

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