MongoDB $addFields Stage

What Is $addFields?

$addFields is a MongoDB aggregation stage that adds one or more computed fields to every document. Existing fields stay by default—so it is the easy way to append columns like lineTotal without rebuilding the whole document.

$addFields = add columns, keep the rest

{ $addFields: { <field>: <expression>, ... } }

keeps all existing fields
same name → overwrites that field
$set → alias for $addFields

vs $project → reshape / pick fields
new fields → visible to later stages

How to Use $addFields in MongoDB

Name the new fields, give each an expression, and place the stage where later steps need those values.

1. Start (or continue) an aggregation pipeline with aggregate([...]).
2. Add { $addFields: { fieldName: <expression> } }.
3. Use field paths like "$price" and operators like $multiply.
4. Use the new fields in later stages ($sort, $group, another $project).

Pseudocode

for each document:
    out = copy(document)          // keep existing fields
    for each (field, expression) in $addFields:
        out[field] = evaluate(expression)
    emit out

Cheat Sheet

Keep these facts handy while adding fields in a pipeline.

Live Preview

Watch $addFields append lineTotal = price × quantity while keeping the original fields.

input:
  { product: "Keyboard", price: 45, quantity: 2 }

$multiply → 45 * 2 = 90

output (+ keeps original fields):
  { product: "Keyboard", price: 45, quantity: 2, lineTotal: 90 }

Worked Walkthrough — Line Total

One order has price: 45 and quantity: 2. Goal: add lineTotal without dropping other fields.

Document in:
  { product: "Keyboard", price: 45, quantity: 2 }

$addFields:
  lineTotal: { $multiply: ["$price", "$quantity"] }

45 * 2 = 90

Document out:
  {
    product: "Keyboard",
    price: 45,
    quantity: 2,
    lineTotal: 90      // new
  }

MongoDB Examples

We use a small orders collection. First add a line total, then add two fields in one stage. Run these in mongosh after inserting the sample data once.

db.orders.insertMany([
  {
    _id: 1,
    product: "Keyboard",
    price: 45,
    quantity: 2,
    firstName: "Sam",
    lastName: "Lee"
  },
  {
    _id: 2,
    product: "Mouse",
    price: 25,
    quantity: 1,
    firstName: "Alex",
    lastName: "Kim"
  },
  {
    _id: 3,
    product: "Monitor",
    price: 180,
    quantity: 1,
    firstName: "Jordan",
    lastName: "Wu"
  }
]);

db.orders.find()

[
  {
    _id: 1,
    product: "Keyboard",
    price: 45,
    quantity: 2,
    firstName: "Sam",
    lastName: "Lee"
  },
  {
    _id: 2,
    product: "Mouse",
    price: 25,
    quantity: 1,
    firstName: "Alex",
    lastName: "Kim"
  },
  {
    _id: 3,
    product: "Monitor",
    price: 180,
    quantity: 1,
    firstName: "Jordan",
    lastName: "Wu"
  }
]

db.orders.aggregate([
  {
    $addFields: {
      lineTotal: { $multiply: ["$price", "$quantity"] }
    }
  }
]);

{
  _id: 1,
  product: "Keyboard",
  price: 45,
  quantity: 2,
  firstName: "Sam",
  lastName: "Lee",
  lineTotal: 90
}
{
  _id: 2,
  product: "Mouse",
  price: 25,
  quantity: 1,
  firstName: "Alex",
  lastName: "Kim",
  lineTotal: 25
}
{
  _id: 3,
  product: "Monitor",
  price: 180,
  quantity: 1,
  firstName: "Jordan",
  lastName: "Wu",
  lineTotal: 180
}

db.orders.aggregate([
  {
    $addFields: {
      lineTotal: { $multiply: ["$price", "$quantity"] },
      fullName: {
        $concat: ["$firstName", " ", "$lastName"]
      }
    }
  }
]);

{
  _id: 1,
  product: "Keyboard",
  price: 45,
  quantity: 2,
  firstName: "Sam",
  lastName: "Lee",
  lineTotal: 90,
  fullName: "Sam Lee"
}

Performance Notes

Expression work is usually cheap compared with large sorts or joins. Filter early with $match when only some documents need the new fields.

Key Takeaways