MongoDB Atlas

Harshit Patidar Oct 08 2020 · 2 min read
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For years now, MongoDB has been the go-to NoSQL database for both individuals and enterprises building large-scale applications. It's open source, easily scalable, and provides high availability. It also supports very complex queries and fine-grained concurrency control.

In recent years, the database industry has undergone a number of changes, resulting in an increased shift towards a database as a service (DBaas) model versus an on-premise infrastructure. Databases are at the core of most business apps, and cloud-based DBaaS services offers users a flexible, scalable, and on-demand platform that eliminates the need to set up costly physical hardware, install software, or configure for performance. In addition, the data companies are analyzing is also changing. Users and developers now look for more adaptable databases that allow them to access and work with unstructured data. Along with this has come a greater demand for in-memory and NoSQL databases with a pay-per-use model. 

MongoDB, the company behind the open source database, sought to fill this need with Atlas, its own DBaaS offering that provides users with a managed database service. The service offers pay-as-you go pricing and allows users to deploy on the cloud service provider of their choice (AWS, Azure, and GCP). Atlas has been a success for MongoDB, and as of 2019 accounts for 35% of its total revenue with over 12,000 customers.


1 -Creating a Cluster 

Click on Create Cluster
Your Cluster will look like it and click on connect 

2 - Create a MongoDB User , IP address and Connect to app 

You can add own IP or Click on Allow Access from Anywhere 
I have given test as username and password give according to you and click Create Database User
Click  on Connect to your application 
Copy Link we will use later

3 - Creating Data Base 

Click on Collection you will see screen below-

Load  Sample Data if you have otherwise create data by Add my Own Data 
Click On Insert Document
For example giving data
You can see we have created data 

4 - Now Connecting with Jupyter Notebook 

pip install pymongo

On terminal type command given above

5 - Now Copy Link we have-

<password> remove and type password you have given above and run it and your app is created on atlas 

6 - Insert New Data in your Cluster 

7 - Summary 

Overall, we found MongoDB Atlas to be easy to use and get acclimated to. The process of registering for an account, deploying your first cluster, and connecting to your cluster was seamless thanks in large part to its intuitive interface. In particular, we liked that Atlas included sample data that we were able to load into our cluster and then utilize the Data Explorer GUI to interact with the data. 

Its simple user interface, along with its host of features including scalability with automatic sharding, built-in automation mechanisms for operational tasks, and excellent performance that provides high throughput and low latency even for the most demanding workloads, and it’s no wonder that experienced developers and new users alike have grown to love MongoDB Atlas.

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