Is your "schemaless" database becoming a "messy" database? While MongoDB is flexible, production apps need data integrity! In this essential guide, we’ll show you how to use JSON Schema Validation to enforce strict rules for your collections, ensuring every document follows your specific structure.

This tutorial is perfect for developers who want to prevent "garbage data" from entering their system. We'll show you how to define required fields, enforce data types, and set value ranges directly at the database level.

What you will learn in this video:

The $jsonSchema Operator: The heart of MongoDB validation. We’ll break down the syntax: bsonType, required, and properties.

Creating a New Validated Collection: Learn how to use db.createCollection() with a validator to ensure your users or products data is perfect from day one.

Validation Levels (Strict vs. Moderate): * Strict (Default): Applies rules to all inserts and updates.

Moderate: Perfect for legacy data! It only validates new documents or updates to existing valid documents.

Validation Actions (Error vs. Warn): * Error (Default): Rejects invalid data immediately.

Warn: Great for testing! It allows the data but logs a warning so you can fix your app logic first.

Updating Rules on Existing Collections: Did your requirements change? We’ll show you how to use the collMod command to add or modify rules without dropping your data.

Handling Complex Data: How to validate nested objects and arrays of strings.

Pro-Tip: Remember that MongoDB treats a missing field as null if you aren't careful. We'll show you how to handle optional fields correctly while still enforcing their type!

By the end of this video, you’ll have a "locked-down" MongoDB collection that rejects invalid inputs, making your backend code cleaner and your data more reliable.

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