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Lenmor Ld
Lenmor Ld

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🌱 Complete REST API with MongoDB Atlas cloud, Node, and Express in 10 minutes

Let's bring the data to the cloud this time! 💾 ☁.
And what better way to do that than a FREE cloud database!
We'll be using the free cluster of Mongo DB Atlas.

What is Mongo DB Atlas?

Mongo DB Atlas is a fully-managed database-as-a-service available on AWS, Azure, and GCP

Before Atlas, I used mLab. mLab was then acquired by MongoDB last year. Pretty much similar to mLab, MongoDB Atlas is the easiest way to have a cloud MongoDB instance.


  • 💲 0 dollars: I am not an advertiser for MongoDB, but I love this service and this one won't break the bank ❌🔨🐖, since... well it's no-strings-attached FREE for up to 512MB. Perfect for small side-projects!

  • 🏃‍♂️ Quick, simple, and fast: no installation and config files. After signing up and creating a cluster (takes 5 minutes), you're all set.

  • It's in the cloud: Not running in your machine as a Mongo service. Not in a disk file like diskdb. You can manage it from anywhere through the Atlas web app. For your app, you only need a connection URL to access the db.

  • 😎 Very cool UI: Atlas dashboard is very intuitive, and first-time users will find it easy to use with the visual cues and steps.

Cloud setup

There might be some slight screenshot differences to the actual Atlas UI by the time you do this, but the described steps should get you to the same results.

1. First sign up here:

2. Create a free tier Starter Cluster

The free Starter Cluster M0 comes with 512 MB Storage, shared RAM and vCPU.

This should be more than enough for our starter Node project.

  • Cluster region: you can pick any provider (AWS, Google, Azure) and the region closest to you that has a Free Tier. For me, it was AWS us-east-1.

  • You can leave the rest at FREE defaults.

  • Create the cluster.

The creation and provisioning might take a few minutes

  • Afterwards, the dashboard appears, with the side panel that contains all the options needed to manage clusters.

3. Connect to the Cluster

Click [Connect] in the Cluster we have just created.

The dialog that appears gives options to:

  1. Whitelist your IP address
  2. Create a MongoDB user

3.1 Whitelist IP Address

Whitelisting means only allowing access to selected (thus trusted) entities

  • [Add Your Current IP address], which should automatically get your current public IP address. Optionally add a description such as "My Home IP address"

    • ❗ Remember to do this step again when you switch WiFi, e.g. when moving from coffee shop to home WiFi.
    • 💡 If you are in a public wi-fi, you can use a service like to get your IPv4 public address, since ipconfig or ifconfig might give you only the internal network address.
    • 💣You can use to enable all IP addresses anywhere, which simplifies this process, but makes it VERY INSECURE.

3.2 Create admin user.

Enter your preferred username and password. This will be the first admin ("root") user, then [Create MongoDB User].

  • Keep these credentials handy, since we'll use them later.

  • Close the window. We'll connect to the cluster later.

4. 📃 Add sample data

From the cluster view, click [Collections], then [Add my Own Data]

  • Same as the last lesson, we use:
    • database name: data
    • collection name: movies

🎥 The movies from this series is from IMDB. You could use the id from any movie page URL. E.g. In "The Lion King" page; id is tt0110357.

Insert Document

  • Insert a movie entry, as before - Leave the given _id provided by Atlas since this is internal

  • Now we see the inserted data in the dashboard. Add more as you wish

Perfect. Now we got data. Time to connect to the cluster

5. 🔌 Connect to cluster

Go back to the Clusters view, then click Connect in our cluster.

Choose [Connect your Application]

Leave the default Node.js version 3+

Copy the Connection String. We'll use this in the next step.

Now we're ready to dive into code!


Connecting to the db

1. Grab the starter code from last lesson here:

  1. Install mongodb driver
$ npm install mongodb

2. Create a new file called db.js in the app root.

Use this snippet, and replace CONNECTION_STRING_FROM_ATLAS with your connection string.

It should look a bit like this

// db.js

// mongodb driver
const MongoClient = require("mongodb").MongoClient;

const dbConnectionUrl = "CONNECTION_STRING_FROM_ATLAS";

function initialize(
) {
    MongoClient.connect(dbConnectionUrl, function(err, dbInstance) {
        if (err) {
            console.log(`[MongoDB connection] ERROR: ${err}`);
            failureCallback(err); // this should be "caught" by the calling function
        } else {
            const dbObject = dbInstance.db(dbName);
            const dbCollection = dbObject.collection(dbCollectionName);
            console.log("[MongoDB connection] SUCCESS");


module.exports = {
  1. The function accepts our cloud db details (db name and collection name) and callbacks.
  2. It then connects to our cloud db using the driver method MongoClient.
  3. Upon success, it calls the successCallback passing the dbCollection object.
    • Any failure will be thrown by failureCallback
  4. We'll use dbCollection to execute mongodb commands.

Back to our server, we'll start server.js from scratch.

We will be using the cloud db connection instead of diskdb.

// server.js

const express = require("express");
const server = express();

const body_parser = require("body-parser");

// parse JSON (application/json content-type)

const port = 4000;

// << db setup >>
const db = require("./db");
const dbName = "data";
const collectionName = "movies";

// << db init >>

server.listen(port, () => {
    console.log(`Server listening at ${port}`);

In << db setup >>, we import db.js (to use our initialize method), and define variables for the db's info.

4. Initialize the database connection.

// db.js
// << db init >>
db.initialize(dbName, collectionName, function(dbCollection) { // successCallback
    // get all items
    dbCollection.find().toArray(function(err, result) {
        if (err) throw err;

    // << db CRUD routes >>

}, function(err) { // failureCallback
    throw (err);

We initialize the db with the dbName, collectionName, and a successCallback.

Inside the successCallback:

  • GET all using collection.find(), which returns a cursor.

    • A cursor is like an iterator, where you can do next, hasNext(), etc
  • Convert the cursor to an array using async method toArray(callback)

    • It's simpler for our use case to return full array, than iterate the cursor.
  • callback runs after successfully converting the cursor to an array

    • We log the result for now, but you can imagine the code for returning response to client goes here

Start server

$ npm install
$ npm start

...which should give:

Server listening at 4000
[MongoDB connection] SUCCESS
[ { _id: 5d7ed8f31c9d4400009c3775,
    id: 'tt0110357',
    name: 'The Lion King',
    genre: 'animation' } ]

Yay! It works!


Now let's complete all the CRUD routes!

CRUD routes

Here's a rundown of the CRUD-to-MongoDB operations for our route handlers.

Notice that there are quite some syntax differences between diskdb functions and the official MongoClient.

CRUD Operation REST operation MongoClient Operation
Create POST /items dbCollection.insertOne(object, callback)
Read One GET /items/:id dbCollection.findOne(query callback)
Read All GET /items dbCollection.find(query).toArray(callback)
Update PUT /items/:id dbCollection.updateOne(query, { $set: obj }, callback)
Delete DELETE /items/:id dbCollection.deleteOne(query, callback)

All of these routes go in the << db CRUD routes >> marker in our code.

i. Create ➕

// server.js
// << db CRUD routes >>"/items", (request, response) => {
    const item = request.body;
    dbCollection.insertOne(item, (error, result) => { // callback of insertOne
        if (error) throw error;
        // return updated list
        dbCollection.find().toArray((_error, _result) => { // callback of find
            if (_error) throw _error;
  1. For the POST /items handler, use insertOne(item, callback) to add the movie from request.body (parsed by body_parser middleware)

  2. In the callback of insertOne, throw the error if any. The result is not used here (_which is just a boolean for success and _id of inserted document).

  3. Get the updated list using find(), and return the _result as the response in its callback.

Note the two levels of similar callbacks here: outer callback of insertOne, and inner one of find. This is why I used (_error, _result) in the inner to avoid name collision. But feel free to rename them 😉


$ curl -X POST -H "Content-Type: application/json" --data '{"id": "tt0109830", "name": "Forrest
Gump", "genre": "drama"}' http://localhost:4000/items

[{"_id":"5de5c9d01c9d440000482ef0","id":"tt0110357","name":"The Lion King","genre":"animation"},{"_id":"5de7009967aec74a90f88d67","id":"tt0109830","name":"Forrest Gump","genre":"drama"}]

ii. Read one 🕵️

server.get("/items/:id", (request, response) => {
    const itemId =;

    dbCollection.findOne({ id: itemId }, (error, result) => {
        if (error) throw error;
        // return item
  1. Get the id directly from the params (e.g. 1234 for http://localhost/items/1234).

  2. Find the item with that id using findOne(query).

query is just an object so you can use key-value pairs for your queries. We use this query object for find, delete and other MongoDB commands.

// query can be:

{ id: 1 }; // find using id

{ name: "The Lion King" }; // find using name

{ id: 1, name: "The Lion King", genre: "action" }; // find using id, name and genre
  1. Return the item in the response


$ curl http://localhost:4000/items/tt0109830

{"_id":"5de7009967aec74a90f88d67","id":"tt0109830","name":"Forrest Gump","genre":"drama"}

iii. Read all 🕵️

server.get("/items", (request, response) => {
    // return updated list
    dbCollection.find().toArray((error, result) => {
        if (error) throw error;

Return all the items in the collection in the response, same in POST /items


$ curl http://localhost:4000/items

[{"_id":"5de5c9d01c9d440000482ef0","id":"tt0110357","name":"The Lion King","genre":"animation"},{"_id":"5de7009967aec74a90f88d67","id":"tt0109830","name":"Forrest Gump","genre":"drama"}]

iv. Update ✏️

server.put("/items/:id", (request, response) => {
    const itemId =;
    const item = request.body;
    console.log("Editing item: ", itemId, " to be ", item);

    dbCollection.updateOne({ id: itemId }, { $set: item }, (error, result) => {
        if (error) throw error;
        // send back entire updated list, to make sure frontend data is up-to-date
        dbCollection.find().toArray(function(_error, _result) {
            if (_error) throw _error;
  1. Get the id from params and the item from body (through body-parser).

  2. Update item with id and set it to item, using dbCollection.updateOne(query, { $set: item }, callback.

  • Note the use of MongoDB-specific { $set: item }
  1. Return the updated list, as in POST /items and GET /items


Maybe you think "The Lion King" is a drama, since ...well, I won't spoil it. 🤫 🦁

curl -X PUT -H "Content-Type: application/json" --data '{"genre": "drama"}' http://localhost:4000/items/tt0110357

[{"_id":"5de5c9d01c9d440000482ef0","id":"tt0110357","name":"The Lion King","genre":"drama"},{"_id":"5de7009967aec74a90f88d67","id":"tt0109830","name":"Forrest Gump","genre":"drama"}]

v. Delete ❌

server.delete("/items/:id", (request, response) => {
    const itemId =;
    console.log("Delete item with id: ", itemId);

    dbCollection.deleteOne({ id: itemId }, function(error, result) {
        if (error) throw error;
        // send back entire updated list after successful request
        dbCollection.find().toArray(function(_error, _result) {
            if (_error) throw _error;

Here, only the id is needed from params, which we pass to dbCollection.deleteOne(query).

As before, you can formulate a query easily to your needs, since it's just an object.

🤸‍♀️ Challenge: modularize the dbCollection.find() since we're using it in 3 places.


$ curl -X DELETE http://localhost:4000/items/tt0109830

[{"_id":"5de5c9d01c9d440000482ef0","id":"tt0110357","name":"The Lion King","genre":"drama"}]


  1. Callbacks ??!!, why this instead of ES6 Promises, or ES7 async/await...
  • MongoClient.connect only supports callbacks, but we'll promisify (and aysnc-await-ify) these callbacks on the next lesson, since honestly they are starting to look like callback hell. See this post for a fun rundown on callback hell.
  1. Why do We return all of the items in the response create, update, delete ?
  • There are a lot of options on what to do to synchronize UI and backend after a change, and it is quite a Software Architecture topic for itself.
  • Here, we just return the updated items to UI after a create, update and delete. We let the frontend (e.g. React, Vue, Angular, Vanilla JS) update its state and views from that information.

Here's the complete Code


"Okay, that was nice. But what can I do with this? "

✅ Serving HTML files
✅ Cloud Database persistence

Now, this is an actual server for a small project. Add more routes, save some data in the db through API requests. Just add frontend!™

Next up:

(In progress)

  • MongoDB callbacks to Promises and Async/Await

This article is part of a Node+Express series I'm working on.

For the meantime, if you can't get enough of Node+Express 🤓,
checkout my Node workshop (Gihub repo and slides):

GitHub logo lenmorld / node_workshop

Build a server and API for your next web application, using Node, Express and MongoDB

Node workshop

to follow workshop:

$ git checkout dev
$ node server.js

to dev latest

$ git checkout master
$ npm start

Create a .env file on root

# API keys go here

Here we discussed:
  • Using Node and Express
  • Routing, request and response
  • Building a REST API
  • Server-rendered templates
  • Connecting to a NoSQL (mongo) database
  • Using external APIs, such as Spotify
  • and much more!

Happy server-ing! 🤓

Now, all this Mongo talk made me hungry.
I'm gonna have some of my favorite "Hopia Mongo" (bean-filled Filipino pastry)🌱.

Hopia Mongo

Photo from FoxyFolksy in article "Hopia Recipe- Munggo And Ube Filling" src:

Top comments (6)

consultantcraig profile image

Thanks for writing this. Your article led to a breakthrough for me on the project I'm working on, though probably not in the context you imagined when writing this so thought I'd share. I have a client that uses MongoDB Atlas for their enterprise-wide system of record. But their analytics team needs the data in tabular format. Atlas has a "BI Connector" that allows querying the cluster's databases with traditional SQL - I imagine behind the scenes they are mapping any document changes out to a relational structure that mirrors the collections. However the fact that the relational structure is being maintained on a moment by moment basis impacts performance. And the BI tool itself has a technical learning curve that these non-tech folks don't want to deal with. They're familiar with SQL Server. So I proposed to write automation that can pipe the data into any system of record in their organization, using node + loopback.js. loopback provides a way to quickly generate an API (REST or GraphQL) and has connectors for almost any kind of data source. The challenge is that I didn't want to hardcode the Atlas document structures into the application, as they are in flux at the moment. I'm building an auto-mapper that can connect to the specified MongoDB database, get its collections and automatically generate SQL tables from them and populate those SQL tables from them, with in-database configuration params to control the filtering e.g. only get last 5 minutes of data from collection X using its .timestamp property. At first I tried using mongoexport.exe which lets you export to flatfiles and it takes in collections and fields as params. But the problem is it exports large numbers in scientific notation format, which loses some of the number! Like, really Mongo devs?? wtf. Just export it as a string if u have to. But nope. Brick wall. Compass has a great csv export which gets the numbers right and doesn't mess them up using scientific notation, but it's not currently automatable, i.e. you can't call its functions from the command line. I knew there had to be a way around this so I just searched for MongoDB Atlas API which dug up your article by accident (i.e. I was looking for an API I could use but no luck then I found your article. And I was like DUH, use the mongodb driver for node! No more scientific notation on bigints, and fully automatable, So thanks! I will still put the code inside loopback.js because it's a fantastically architected framework for modularizing your code into services and exposing those via API. I'm not here to sell loopback.js but I love it. And I'm always open to other ideas even if you think there's a much better way to do what I'm trying to accomplish here. Have a good one!

simsushare profile image
Jonathan Kaye

Hi Lenmor, great tutorial exactly what I needed as a start for my analytics. Easy and quick to go through. One update you might want to make to the mongo connect invocation is to add a couple options to avoid the deprecation warning about the Server Discovery and Monitoring engine.

// db.js
useNewUrlParser: true,
useUnifiedTopology: true

Should be easy to figure out for viewers. Again, thanks so much!

elletownsend profile image
Elle Townsend🎄

I was looking through so many similar tutorials on this exact topic, scratching my head and struggling so much with this, but this tutorial is everything I needed all in one place! Although the other tutorials claimed to be 'beginner' level, even with 3 years studying computer science I couldn't get them to work, but this well-documented guide with images and explanations is by far the best one I've seen for this implementation. Thank you SO much for writing this !! It has saved my project!!!

lennythedev profile image
Lenmor Ld • Edited

I'm happy it helped :)

Thanks for taking the time to write a reply. I appreciate it!

yuman profile image

This is amazing clear, simple and practical. It worked on my first try. Thank you very much.

tobiastotz profile image
Tobias Totz

Hey Lenmor, thank you for this great article!
I will definitly try this out :)