How to Start Using MongoDB as a Beginner

MongoDB provides an easy way to host and manage data in the cloud. This tutorial delves into the inner workings of installing and setting up the platform. As MongoDB is open-source, plenty of how-to guides and walk-throughs will help a beginner learn how to insert, query, and delete data in MongoDB.

Here is where you can start deploying this advanced platform for your needs.

Table of Contents

Create an Account

To start the MongoDB Atlas setup, create an account. This will register you with a MongoDB Database-as-a-Service that can be accessed through your web browser. All three major cloud providers can install MongoDB Atlas. With a few clicks on Amazon Web Services, Microsoft Azure, or Google Cloud Platform, you will have a fully functioning MongoDB database ready.

Set Up Your Deployment

To deploy MongoDB, opt for a tier-free solution or local installation. The free tier cluster on MongoDB Atlas provides a fast, easy, and completely affordable way to start using the platform. It is often the case that beginners choose.

After MongoDB installed, create a project. Then, create a MongoDB cluster. Once your cluster is up, it’s time to set up your IP allowlist addresses and database users. To whitelist an IP, click ‘Add Your Current IP Address’ and set up a username and password. Next, connect with the Mongo shell option.

Connecting to a MongoDB Cluster

There are multiple ways to connect to a MongoDB cluster. The first step is to install the mongo shell. The second is to download and use Compass from the MongoDB downloads page. You can also download and install MongoDB Community Edition or Enterprise Edition.

MongoDB works if you inspect your clusters’ status from the home page and see everything running as intended.

Creating Your First Collection

Once you’ve created your first collection, the process is simple. The GUI will guide you through this, especially with Compass. After your collection is created, you insert your first document. All documents are automatically stored in binary format, aka BSON, speeding up retrieval and access times.

Exploring MongoDB Capabilities and Interactions

MongoDB has many ways to interact. The user should decide what’s best for them based on their existing knowledge.

Use Compass, a cross-platform GUI officially released for MongoDB.
Use the web browser interface, which is similar to Compass.
Use the command line tool, aka the mongo shell.
Use a programming language, API, or IDE.

In addition, MongoDB documents follow the Javascript Object Notation (JSON) format. Data fields can be arbitrary numbers and types.

Translating SQL to MongoDB

Anyone who has used SQL before will benefit from MongoDB. However, the terms have been modified slightly.

A table becomes a row.
A row becomes a document.
Join is $lookup
While traditional SQL uses multiple nodes, MongoDB uses one machine.

SQL tables define the structure of a data set. MongoDB contains collections and text documents with name-value pairs. While in SQL or any relational database, tables are related by keys, MongoDB collections contain unstructured and potentially arbitrary data. MongoDB supports indexes, like SQL.

Filtering Records with Common Filter Operators

Just like one would use a programming language to filter certain values, MongoDB accomplishes the same in much the same way. Use common filter operators, such as numerical and string querying comparisons. MongoDB also supports query and projection operators and update operators to take things further and aggregate.

Always Configure Indexes for Collections

It is good to always configure indexes for collections. If queries use specific fields, MongoDB will not have to scan every document to get the result. Based on the defined index, it will look like this: This dramatically decreases retrieval time and increases operational efficiency. For collections that are excessively large or on the verge of future growth, configuring indexes is something you will want to do.

Enable Replica Sets and Sharding

Replica sets are when a copy of data is created and stored on another server. Sharding is a separate feature that distributes a collection of documents in multiple instances, aka horizontal scaling. Enabling one or the other, or both is smart. It ensures that data for the end-user is protected and kept safe when there is maintenance or should your database fail.