Structure your Data for MongoDB

Deployment Type:

Author: MongoDB Documentation Team

Welcome to the Getting Started guides. This guide will show you how to structure data for MongoDB.

Time required: 15 minutes

What You’ll Need

  • An idea of what data you’d like to store

Check Your Environment

  • There are no technical requirements for this guide.



Define Your Data Set

When setting up a data store, your first task is to answer the question: “What data would I like to store and how do the fields relate to each other?”.

This guide uses a hypothetical inventory database to track items and their quantities, sizes, tags, and ratings.

Here is an example of the types of fields you might wish to capture:

name quantity size status tags rating
journal 25 14x21,cm A brown, lined 9
notebook 50 8.5x11,in A college-ruled,perforated 8
paper 100 8.5x11,in D watercolor 10
planner 75 22.85x30,cm D 2019 10
postcard 45 10x,cm D double-sided,white 2

Start Thinking in JSON

While a table might seem like a good place to store data, as you can see from the example above, there are fields in this data set that require multiple values and would not be easy to search or display if modeled in a single column (for example – size and tags).

In a SQL database you might solve this problem by creating a relational table.

In MongoDB, data is stored as documents. These documents are stored in MongoDB in JSON (JavaScript Object Notation) format. JSON documents support embedded fields, so related data and lists of data can be stored with the document instead of an external table.

JSON is formatted as name/value pairs. In JSON documents, fieldnames and values are separated by a colon, fieldname and value pairs are separated by commas, and sets of fields are encapsulated in “curly braces” ({}).

If you wanted to begin to model one of the rows above, for example this one:

name quantity size status tags rating
notebook 50 8.5x11,in A college-ruled,perforated 8

You might start with the name and quantity fields. In JSON these fields would look like:

{"name": "notebook", "qty": 50}

Identify Candidates for Embedded Data and Model Your Data

Next you will decide which fields require multiple values. These fields will be candidates for embedded documents or lists/arrays of embedded documents within the document.

For example, in the data above, size might consist of three fields:

{ "h": 11, "w": 8.5, "uom": "in" }

And some items have multiple ratings, so ratings might be represented as a list of documents containing the field scores:

[ { "score": 8 }, { "score": 9 } ]

And you might need to handle multiple tags per item. So you might store them in a list too.

[ "college-ruled", "perforated" ]

Finally, a JSON document that stores an inventory item might look like this:

 "name": "notebook",
 "qty": 50,
 "rating": [ { "score": 8 }, { "score": 9 } ],
 "size": { "height": 11, "width": 8.5, "unit": "in" },
 "status": "A",
 "tags": [ "college-ruled", "perforated"]

This looks very different from the tabular data structure you started with in Step 1.


It’s a JSON standard to quote field names.


Congratulations. You now have an idea of how to structure your data using a JSON document.

What’s Next

Next you’ll set up a MongoDB instance. Choose one of the following options:

See Also


This guide is intended for new learners of MongoDB. For more in-depth information, see The MongoDB Server Manual.