MongoDB Best Practices

Introduction

MongoDB is forgiving — and that's a trap. Bad schemas, missing indexes and over-broad queries silently work in development and then implode in production. This lesson is the cheat sheet senior engineers wish they had on day one.

Understanding the topic

The cardinal best practices:

• 🔎 Always explain() a new query before shipping it.
• 📐 Design for read patterns first — write code, then model.
• 🧱 Prefer embedding for 1:few; referencing for 1:many or many:many.
• 🗝 Add a unique index on every natural key (email, slug, sku).
• 💰 Use NumberDecimal for money.
• ⚡ Use covered queries — projection that matches an index = zero document fetch.
• 🔐 Never expose Mongo to the internet without auth, TLS and IP restrictions.

Real-world use

The difference between a $50/month and a $5,000/month Atlas bill is usually 3 missing indexes and one runaway aggregation.

Best practices

• Profile slow queries with db.setProfilingLevel(1, 100).
• Cap result sets with limit() — never return unbounded data.
• Use the Atlas Performance Advisor; it's free and excellent.

Common mistakes

• Treating MongoDB like 'schemaless' — schema design still matters, you just enforce it in code.
• Forgetting to add indexes before launch — easy to test, costly under load.