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Schema Validation

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MongoDB provides the capability to perform schema validation during updates and insertions.

Specify Validation Rules

Validation rules are on a per-collection basis.

To specify validation rules when creating a new collection, use db.createCollection() with the validator option.

To add document validation to an existing collection, use collMod command with the validator option.

MongoDB also provides the following related options:

  • validationLevel option, which determines how strictly MongoDB applies validation rules to existing documents during an update.
  • validationAction option, which determines whether MongoDB should error and reject documents that violate the validation rules or warn about the violations in the log but allow invalid documents.

JSON Schema

MongoDB supports JSON Schema validation. To specify JSON Schema validation, use the $jsonSchema operator in your validator expression.

Note

JSON Schema is the recommended means of performing schema validation.

For example, the following example specifies validation rules using JSON schema:

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db.createCollection("students", {
   validator: {
      $jsonSchema: {
         bsonType: "object",
         required: [ "name", "year", "major", "address" ],
         properties: {
            name: {
               bsonType: "string",
               description: "must be a string and is required"
            },
            year: {
               bsonType: "int",
               minimum: 2017,
               maximum: 3017,
               description: "must be an integer in [ 2017, 3017 ] and is required"
            },
            major: {
               enum: [ "Math", "English", "Computer Science", "History", null ],
               description: "can only be one of the enum values and is required"
            },
            gpa: {
               bsonType: [ "double" ],
               description: "must be a double if the field exists"
            },
            address: {
               bsonType: "object",
               required: [ "city" ],
               properties: {
                  street: {
                     bsonType: "string",
                     description: "must be a string if the field exists"
                  },
                  city: {
                     bsonType: "string",
                     description: "must be a string and is required"
                  }
               }
            }
         }
      }
   }
})

For more information, see $jsonSchema.

bsonType definitions can be found on the BSON Types page.

Other Query Expressions

In addition to JSON Schema validation that uses the $jsonSchema query operator, MongoDB supports validation with other query operators, with the exception of:

For example, the following example specifies validator rules using the query expression:

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db.createCollection( "contacts",
   { validator: { $or:
      [
         { phone: { $type: "string" } },
         { email: { $regex: /@mongodb\.com$/ } },
         { status: { $in: [ "Unknown", "Incomplete" ] } }
      ]
   }
} )

See also

query operators

Behavior and Examples

Validation occurs during updates and inserts. When you add validation to a collection, existing documents do not undergo validation checks until modification.

Validation on Existing Documents

To perform validation checks on existing documents, use the validate command or the db.collection.validate() shell helper.

The validationLevel option determines which operations MongoDB applies the validation rules:

  • If the validationLevel is strict (the default), MongoDB applies validation rules to all inserts and updates.
  • If the validationLevel is moderate, MongoDB applies validation rules to inserts and to updates to existing documents that already fulfill the validation criteria. With the moderate level, updates to existing documents that do not fulfill the validation criteria are not checked for validity.

For example, create a contacts collection with the following documents:

copy 
db.contacts.insertMany([
   { "_id": 1, "name": "Anne", "phone": "+1 555 123 456", "city": "London", "status": "Complete" },
   { "_id": 2, "name": "Ivan", "city": "Vancouver" }
])

Issue the following command to add a validator to the contacts collection:

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db.runCommand( {
   collMod: "contacts",
   validator: { $jsonSchema: {
      bsonType: "object",
      required: [ "phone", "name" ],
      properties: {
         phone: {
            bsonType: "string",
            description: "phone must be a string and is required"
         },
         name: {
            bsonType: "string",
            description: "name must be a string and is required"
         }
      }
   } },
   validationLevel: "moderate"
} )

The contacts collection now has a validator with the moderate validationLevel:

  • If you attempted to update the document with _id: 1, MongoDB would apply the new validation rules since the existing document matches the criteria.
  • In contrast, MongoDB will not apply validation rules to updates to the document with _id: 2 as it does not meet the validation rules.

Starting in MongoDB version 5.0, the validator returns detailed error information when a validation condition isn’t met. The error output is exhaustive - all errors are reported, not just the first one.

Important

The error output is intended for human consumption. It may change in the future and should not be relied upon in scripts.

In the next example, neither of the updates is consistent with the validation rule we created above that requires name to be a string.

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db.contacts.updateOne(
   { _id: 1 },
   { $set: { name: 10 } }
)

db.contacts.updateOne(
   { _id: 2 },
   { $set: { name: 20 } }
)

The output below shows that the document with _id: 1 fails validation with a detailed explanation, as shown in the errInfo object. The update succeeds for the document with _id: 2 since this document did not meet the initial criteria when validation was added.

// _id: 1
MongoServerError: Document failed validation
Additional information: {
failingDocumentId: 1,
details: {
   operatorName: '$jsonSchema',
   schemaRulesNotSatisfied: [
      {
      operatorName: 'properties',
      propertiesNotSatisfied: [
         {
            propertyName: 'name',
            description: 'name must be a string and is required',
            details: [
            {
               operatorName: 'bsonType',
               specifiedAs: { bsonType: 'string' },
               reason: 'type did not match',
               consideredValue: 10,
               consideredType: 'int'
            }
            ]
         }
      ]
      }
   ]
}
}

// _id: 2
{
   acknowledged: true,
   insertedId: null,
   matchedCount: 1,
   modifiedCount: 0,
   upsertedCount: 0
}

To disable validation entirely, you can set validationLevel to off.

Accept or Reject Invalid Documents

The validationAction option determines how MongoDB handles documents that violate the validation rules:

  • If the validationAction is error (the default), MongoDB rejects any insert or update that violates the validation criteria.
  • If the validationAction is warn, MongoDB logs any violations but allows the insertion or update to proceed.

For example, create a contacts2 collection with the following JSON Schema validator:

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db.createCollection( "contacts2", {
   validator: { $jsonSchema: {
      bsonType: "object",
      required: [ "phone" ],
      properties: {
         phone: {
            bsonType: "string",
            description: "must be a string and is required"
         },
         email: {
            bsonType : "string",
            pattern : "@mongodb\.com$",
            description: "must be a string and match the regular expression pattern"
         },
         status: {
            enum: [ "Unknown", "Incomplete" ],
            description: "can only be one of the enum values"
         }
      }
   } },
   validationAction: "warn"
} )

For example, the following insert operation violates the validation rule:

copy 
db.contacts2.insertOne( { name: "Amanda", status: "Updated" } )

However, since the validationAction is warn, MongoDB only logs the validation violation message and allows the operation to proceed. Run the following command to view the MongoDB logs:

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db.adminCommand( { getLog: "global" } )

Depending on collection usage, this command might return a lot of data. The validation error (one long line in the log, reformatted here for readability) contains information like this:

"{\"t\":{\"$date\":\"2021-01-20T15:59:57.305+00:00\"},
 \"s\":\"W\",
 \"c\":\"STORAGE\",
 \"id\":20294,
 \"ctx\":\"conn1\",
 \"msg\":\"Document would fail validation\",
 \"attr\":{\"namespace\":\"test.contacts2\",
   \"document\":{\"_id\":{\"$oid\":\"6008537d42e0d23385568881\"},
         \"name\":\"Amanda\",
         \"status\":\"Updated\"},
    \"errInfo\":{\"failingDocumentId\":{\"$oid\":\"6008537d42e0d23385568881\"},
         \"details\":{\"operatorName\":\"$jsonSchema\",
              \"schemaRulesNotSatisfied\":[
                  {\"operatorName\":\"properties\",
                    \"propertiesNotSatisfied\":[
                        {\"propertyName\":\"status\",
                         \"details\":[
                              {\"operatorName\":\"enum\",
                               \"specifiedAs\":{\"enum\":[
                                    \"Unknown\",
                                    \"Incomplete\"]},
                          \"reason\":\"value was not found in enum\",
                          \"consideredValue\":\"Updated\"}]}]},
 {\"operatorName\":\"required\",
 \"specifiedAs\":{\"required\":[\"phone\"]},
     \"missingProperties\":[\"phone\"]}]}}}}"

Use Title and Description Fields to Clarify Validation Rules

Starting in MongoDB 5.1, when a document fails schema validation, MongoDB includes the validation title and description in the error response. You can use these fields to provide a clearer explanation of the validation when the rules are not immediately clear, such as when using regular expressions.

Consider a users collection with the following schema validation:

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db.runCommand( {
   collMod: "users",
   validator: { $jsonSchema: {
      bsonType: "object",
      title: "Email validation",
      properties: {
         email: {
            "bsonType": "string",
            "pattern": "^@mongodb\.com$",
            "description": "Email address must end with '@mongodb.com'"
         },
      }
   } },
   validationLevel: "moderate"
} )

The pattern field indicates that all email fields must end with @mongodb.com. If you try to insert a document that does not match the pattern, MongoDB includes the validation title and description in the error output:

Input:

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db.users.insertOne( { "name": "Amelia Morrison", "email": "a.morrison@nwsueicn.com" } )

Output:

MongoServerError: Document failed validation
Additional information: {
  failingDocumentId: ObjectId("614a10bab93bbd15dd2e2eb6"),
  details: {
    operatorName: '$jsonSchema',
    title: 'Email validation',
    schemaRulesNotSatisfied: [
      {
        operatorName: 'properties',
        propertiesNotSatisfied: [
          {
            propertyName: 'email',
            description: "Email address must end with '@mongodb.com'",
            details: [
              {
                operatorName: 'pattern',
                specifiedAs: { pattern: '^@mongodb.com$' },
                reason: 'regular expression did not match',
                consideredValue: 'a.morrison@nwsueicn.com'
              }
            ]
          }
        ]
      }
    ]
  }
}

Note

The validation error output is formatted differently in the legacy mongo shell.

Restrictions

You cannot specify a validator for collections in the admin, local, and config databases.

You cannot specify a validator for system.* collections.

Bypass Document Validation

Users can bypass document validation using the bypassDocumentValidation option.

The following commands can bypass validation per operation using the new option bypassDocumentValidation:

For deployments that have enabled access control, to bypass document validation, the authenticated user must have bypassDocumentValidation action. The built-in roles dbAdmin and restore provide this action.

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