Data Modeling

Introduction

Data modeling in MongoDB is the craft of turning real-world entities into documents that fit your queries. Unlike SQL, where normalization is the default, MongoDB rewards denormalization for read patterns.

Understanding the topic

Modeling principles:

• Design for the dominant read pattern.
• Duplicate small, slow-changing data when it speeds up reads.
• Avoid joins on hot paths — embed instead.
• Use $lookup for occasional or admin queries.
• Plan for growth — bounded arrays, separate collections for hot vs cold data.

Real-world use

An order document might embed a snapshot of the customer's name + shipping address at the time of purchase, so historical orders stay stable even if the customer profile changes.

Best practices

• Use the 'Six Rules of Thumb' from MongoDB's modeling guide.
• Snapshot critical fields you don't want to change retroactively.