Schema Validation

MongoDB's schema is flexible by default — but flexibility without guardrails can lead to inconsistent data. Schema validation lets you enforce structure and data integrity using JSON Schema, without giving up MongoDB's flexibility entirely.

1. Why Validate?

• Prevent malformed documents (missing required fields, wrong types)
• Catch bugs early — at the database layer, not just the application layer
• Document your schema intentions directly in the database

2. Creating a Collection with Validation

db.createCollection("employees", {
  validator: {
    $jsonSchema: {
      bsonType: "object",
      required: ["name", "email", "department"],
      properties: {
        name: { bsonType: "string", description: "must be a string and is required" },
        email: {
          bsonType: "string",
          pattern: "^.+@.+$",
          description: "must be a valid email address"
        },
        department: {
          enum: ["Engineering", "Sales", "HR", "Marketing"],
          description: "must be one of the enum values"
        },
        age: {
          bsonType: "int",
          minimum: 18,
          maximum: 65,
          description: "must be an integer between 18 and 65"
        }
      }
    }
  }
})

3. Validation Levels and Actions

4. Adding Validation to an Existing Collection

db.runCommand({
  collMod: "employees",
  validator: {
    $jsonSchema: {
      bsonType: "object",
      required: ["name", "email"]
    }
  },
  validationLevel: "moderate"
})

5. Testing Validation

// This insert fails validation (missing required "department")
db.employees.insertOne({ name: "Kabir Singh", email: "kabir@example.com" })

// MongoServerError: Document failed validation

6. Schema Validation Checklist

• ✅ Define required fields and types with $jsonSchema
• ✅ Use enum for restricted value sets
• ✅ Choose validationLevel and validationAction appropriately
• ✅ Apply validation to existing collections with collMod