5 Ways to Implement Email Validation in Mongoose

Validating emails in Mongoose is a key step for maintaining clean data and reliable user accounts. We will walk through five ways to implement validation using working code snippets, discuss the shortcomings of these traditional methods, and then show how Abstract API addresses these issues.

How to Implement Email Validation in Mongoose

Mongoose offers several ways to validate email formats directly within your schema definition. Here are four common approaches, each with its own implementation style and level of abstraction.

Built-in Match Validator

A String path in a Mongoose schema can take a match option. This option uses a regular expression to check the validity of the email format. Mongoose wraps the expression in RegExp.test() and runs it each time the document undergoes validation.

const userSchema = new mongoose.Schema({
  email: {
    type: String,
    required: true,
    lowercase: true,
    trim: true,
    match: /^[^\s@]+@[^\s@]+\.[^\s@]+$/
  }
});

Inline Custom Validator Function

The validate property accepts an object that contains a validator function and a message. This method provides full control over the validation logic and can even return a Promise for asynchronous operations.

You can branch on different conditions or perform complex checks before the document saves to MongoDB. The function receives the value to validate as an argument.

const EMAIL_RX = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;
const userSchema = new mongoose.Schema({
  email: {
    type: String,
    required: true,
    lowercase: true,
    validate: {
      validator: v => EMAIL_RX.test(v),
      message: p => `${p.value} is not RFC-5322 compliant`
    }
  }
});

Validator.js Integration

You can integrate a third-party library like validator.js for more nuanced validation. This approach delegates rule maintenance to the library's team, so you do not need to track RFC updates yourself.

The library's isEmail function handles complexities like Unicode characters and display-name strips. You use it inside the same validate hook as an inline custom validator.

const validator = require('validator');
const userSchema = new mongoose.Schema({
  email: {
    type: String,
    required: true,
    lowercase: true,
    validate: {
      validator: v => validator.isEmail(v, { allow_utf8_local_part: false }),
      message: p => `${p.value} fails validator.js isEmail()`
    }
  }
});

Dedicated Schema-Type Plugin

The mongoose-type-email plugin registers a dedicated Email type with Mongoose. This method keeps the schema definition clean, as you just select a different type instead of the addition of custom validators.

The plugin offers built-in options, such as correctTld to reject bare domains and allowBlank. This type can be reused across multiple schemas without the need to copy code.

require('mongoose-type-email');
const userSchema = new mongoose.Schema({
  email: {
    type: mongoose.SchemaTypes.Email,
    required: true,
    correctTld: true,
    allowBlank: false
  }
});

Challenges of Mongoose Email Validation

While these methods provide basic checks, they come with significant challenges. Their focus on syntax alone often fails to ensure data quality and can create maintenance overhead for your application.

• Regex-based approaches like the built-in match validator only confirm syntactic correctness. They cannot detect dead mailboxes or disposable domains because they perform no check on an email's existence or deliverability.
• Static regexes in built-in and custom validators quickly become outdated. They fail to handle new TLDs or Unicode local parts, which causes the rejection of valid emails or the acceptance of invalid ones.
• The common unique: true flag is not a validator but an asynchronous index operation. Duplicate emails can enter the database during concurrent writes, which surfaces later as a database error that requires manual translation.
• A true validation, like an MX lookup, requires an async custom validator. This approach adds network latency and new failure modes to the save pipeline, which can stall or abort document writes entirely.