Problem Statement
How does schema validation work in MongoDB and what are its practical applications?
Explanation
Schema validation in MongoDB allows you to enforce document structure and data types despite MongoDB being schema-less by default. This provides a balance between flexibility and data integrity, ensuring critical fields meet specific requirements while allowing schema evolution.
You define validation rules using JSON Schema syntax when creating or modifying collections. The validator specifies required fields, data types using bsonType, string patterns using regex, numeric ranges with minimum and maximum, and nested document structures. MongoDB validates documents against these rules during insert and update operations.
Validation level determines when rules are applied. Strict validation applies rules to all inserts and updates, rejecting any documents that do not match. Moderate validation applies rules only to new documents and updates to existing valid documents, but allows updates to existing invalid documents. This is useful when adding validation to collections with existing data.
Validation action determines what happens when validation fails. Error action rejects the operation and returns an error to the application. Warn action logs a warning in MongoDB logs but allows the operation to proceed. Warn is useful during development or when gradually introducing validation.
Practical applications include ensuring email fields contain valid email patterns, enforcing required fields like user IDs or timestamps, validating numeric ranges like age between 0 and 150, ensuring enum-like fields contain only allowed values, and validating nested document structures.
Schema validation is particularly valuable in applications where data quality is critical, when multiple applications access the same database and need consistent data formats, during migrations when transitioning from loose to strict schemas, or for compliance requirements that mandate certain data fields.
Validation complements application-level validation. Use MongoDB validation for critical structural requirements and data integrity, while application-level validation handles business logic, user feedback, and complex cross-field validations.