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MongoDB Atlas

Deploy and scale a MongoDB cluster in the cloud with just a few clicks

What is MongoDB Atlas?

MongoDB Atlas is a global cloud database service built and run by the team behind MongoDB. Enjoy the flexibility and scalability of a document database, with the ease and automation of a fully managed service on your preferred cloud.
MongoDB Atlas is a tool in the MongoDB Hosting category of a tech stack.

Who uses MongoDB Atlas?

Companies
97 companies reportedly use MongoDB Atlas in their tech stacks, including Clever, Mixmax for Web, and MongoDB.

Developers
287 developers on StackShare have stated that they use MongoDB Atlas.

Why developers like MongoDB Atlas?

Here鈥檚 a list of reasons why companies and developers use MongoDB Atlas
Private Decisions at about MongoDB Atlas
Private to your company

Here are some stack decisions, common use cases and reviews by members of with MongoDB Atlas in their tech stack.

MongoDB Atlas
MongoDB Atlas

Server application hosted on OpenShift is connecting to MongoDB Atlas to perform database operations. MongoDB Atlas

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Matt Welke
Matt Welke
Software Developer at GroupBy Inc. | 1 upvotes 14.7K views
MongoDB Atlas
MongoDB Atlas

When creating small proofs of concept or personal projects with document data models, that require a lot of data storage but don't warrant paying for hosting, I use Atlas because of the 500 MB free tier and ease of setup.

Often paired with AWS Lambda or Google Cloud Functions. MongoDB Atlas

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MongoDB Atlas
MongoDB Atlas

Persistence layer MongoDB Atlas

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Praveen Mooli
Praveen Mooli
Engineering Manager at Taylor and Francis | 12 upvotes 705.6K views
MongoDB Atlas
MongoDB Atlas
Java
Java
Spring Boot
Spring Boot
Node.js
Node.js
ExpressJS
ExpressJS
Python
Python
Flask
Flask
Amazon Kinesis
Amazon Kinesis
Amazon Kinesis Firehose
Amazon Kinesis Firehose
Amazon SNS
Amazon SNS
Amazon SQS
Amazon SQS
AWS Lambda
AWS Lambda
Angular 2
Angular 2
RxJS
RxJS
GitHub
GitHub
Travis CI
Travis CI
Terraform
Terraform
Docker
Docker
Serverless
Serverless
Amazon RDS
Amazon RDS
Amazon DynamoDB
Amazon DynamoDB
Amazon S3
Amazon S3
#Backend
#Microservices
#Eventsourcingframework
#Webapps
#Devops
#Data

We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.

To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas

To build #Webapps we decided to use Angular 2 with RxJS

#Devops - GitHub , Travis CI , Terraform , Docker , Serverless

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Public Decisions about MongoDB Atlas

Here are some stack decisions, common use cases and reviews by companies and developers who chose MongoDB Atlas in their tech stack.

Gregory Koberger
Gregory Koberger
Founder | 13 upvotes 124.9K views
atReadMe.ioReadMe.io
MongoDB
MongoDB
MySQL
MySQL
PostgreSQL
PostgreSQL
MongoDB Atlas
MongoDB Atlas
MongoLab
MongoLab
Compose
Compose

We went with MongoDB , almost by mistake. I had never used it before, but I knew I wanted the *EAN part of the MEAN stack, so why not go all in. I come from a background of SQL (first MySQL , then PostgreSQL ), so I definitely abused Mongo at first... by trying to turn it into something more relational than it should be. But hey, data is supposed to be relational, so there wasn't really any way to get around that.

There's a lot I love about MongoDB, and a lot I hate. I still don't know if we made the right decision. We've been able to build much quicker, but we also have had some growing pains. We host our databases on MongoDB Atlas , and I can't say enough good things about it. We had tried MongoLab and Compose before it, and with MongoDB Atlas I finally feel like things are in a good place. I don't know if I'd use it for a one-off small project, but for a large product Atlas has given us a ton more control, stability and trust.

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Praveen Mooli
Praveen Mooli
Engineering Manager at Taylor and Francis | 12 upvotes 705.6K views
MongoDB Atlas
MongoDB Atlas
Java
Java
Spring Boot
Spring Boot
Node.js
Node.js
ExpressJS
ExpressJS
Python
Python
Flask
Flask
Amazon Kinesis
Amazon Kinesis
Amazon Kinesis Firehose
Amazon Kinesis Firehose
Amazon SNS
Amazon SNS
Amazon SQS
Amazon SQS
AWS Lambda
AWS Lambda
Angular 2
Angular 2
RxJS
RxJS
GitHub
GitHub
Travis CI
Travis CI
Terraform
Terraform
Docker
Docker
Serverless
Serverless
Amazon RDS
Amazon RDS
Amazon DynamoDB
Amazon DynamoDB
Amazon S3
Amazon S3
#Backend
#Microservices
#Eventsourcingframework
#Webapps
#Devops
#Data

We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.

To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas

To build #Webapps we decided to use Angular 2 with RxJS

#Devops - GitHub , Travis CI , Terraform , Docker , Serverless

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Jeyabalaji Subramanian
Jeyabalaji Subramanian
CTO at FundsCorner | 12 upvotes 79.4K views
atFundsCornerFundsCorner
PostgreSQL
PostgreSQL
MongoDB
MongoDB
MongoDB Atlas
MongoDB Atlas

Database is at the heart of any technology stack. It is no wonder we spend a lot of time choosing the right database before we dive deep into product building.

When we were faced with the question of what database to choose, we set the following criteria: The database must (1) Have a very high transaction throughput. We wanted to err on the side of "reads" but not on the "writes". (2) be flexible. I.e. be adaptive enough to take - in data variations. Since we are an early-stage start-up, not everything is set in stone. (3) Fast & easy to work with (4) Cloud Native. We did not want to spend our time in "ANY" infrastructure management.

Based on the above, we picked PostgreSQL and MongoDB for evaluation. We tried a few iterations on hardening the data model with PostgreSQL, but realised that we can move much faster by loosely defining the schema (with just a few fundamental principles intact).

Thus we switched to MongoDB. Before diving in, we validated a few core principles such as: (1) Transaction guarantee. Until 3.6, MongoDB supports Transaction guarantee at Document level. From 4.0 onwards, you can achieve transaction guarantee across multiple documents.

(2) Primary Keys & Indexing: Like any RDBMS, MongoDB supports unique keys & indexes to ensure data integrity & search ability

(3) Ability to join data across data sets: MongoDB offers a super-rich aggregate framework that enables one to filter and group data

(4) Concurrency handling: MongoDB offers specific operations (such as findOneAndUpdate), which when coupled with Optimistic Locking, can be used to achieve concurrency.

Above all, MongoDB offers a complete no-frills Cloud Database as a service - MongoDB Atlas. This kind of sealed the deal for us.

Looking back, choosing MongoDB with MongoDB Atlas was one of the best decisions we took and it is serving us well. My only gripe is that there must be a way to scale-up or scale-down the Atlas configuration at different parts of the day with minimal downtime.

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Abdullah Amin
Abdullah Amin
MongoDB
MongoDB
ExpressJS
ExpressJS
Node.js
Node.js
React
React
Redis
Redis
Heroku
Heroku
Mongoose
Mongoose
MongoDB Atlas
MongoDB Atlas
Cloudinary
Cloudinary
Twilio SendGrid
Twilio SendGrid
JSON Web Token
JSON Web Token
Passport
Passport
PayPal
PayPal
Redux
Redux
Git
Git
Slack
Slack
Visual Studio Code
Visual Studio Code
Postman
Postman

Repost

Overview: To put it simply, we plan to use the MERN stack to build our web application. MongoDB will be used as our primary database. We will use ExpressJS alongside Node.js to set up our API endpoints. Additionally, we plan to use React to build our SPA on the client side and use Redis on the server side as our primary caching solution. Initially, while working on the project, we plan to deploy our server and client both on Heroku . However, Heroku is very limited and we will need the benefits of an Infrastructure as a Service so we will use Amazon EC2 to later deploy our final version of the application.

Serverside: nodemon will allow us to automatically restart a running instance of our node app when files changes take place. We decided to use MongoDB because it is a non relational database which uses the Document Object Model. This allows a lot of flexibility as compared to a RDMS like SQL which requires a very structural model of data that does not change too much. Another strength of MongoDB is its ease in scalability. We will use Mongoose along side MongoDB to model our application data. Additionally, we will host our MongoDB cluster remotely on MongoDB Atlas. Bcrypt will be used to encrypt user passwords that will be stored in the DB. This is to avoid the risks of storing plain text passwords. Moreover, we will use Cloudinary to store images uploaded by the user. We will also use the Twilio SendGrid API to enable automated emails sent by our application. To protect private API endpoints, we will use JSON Web Token and Passport. Also, PayPal will be used as a payment gateway to accept payments from users.

Client Side: As mentioned earlier, we will use React to build our SPA. React uses a virtual DOM which is very efficient in rendering a page. Also React will allow us to reuse components. Furthermore, it is very popular and there is a large community that uses React so it can be helpful if we run into issues. We also plan to make a cross platform mobile application later and using React will allow us to reuse a lot of our code with React Native. Redux will be used to manage state. Redux works great with React and will help us manage a global state in the app and avoid the complications of each component having its own state. Additionally, we will use Bootstrap components and custom CSS to style our app.

Other: Git will be used for version control. During the later stages of our project, we will use Google Analytics to collect useful data regarding user interactions. Moreover, Slack will be our primary communication tool. Also, we will use Visual Studio Code as our primary code editor because it is very light weight and has a wide variety of extensions that will boost productivity. Postman will be used to interact with and debug our API endpoints.

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Antonio Sanchez
Antonio Sanchez
CEO at Kokoen GmbH | 6 upvotes 17.2K views
atKokoen GmbHKokoen GmbH
MongoDB
MongoDB
MongoDB Atlas
MongoDB Atlas
#MongoDB

After getting the first 400 registered users at https://tool-seo.com, we have decided to switch from the self-hosted version of MongoDB to MongoDB Atlas This decision was taken in order to reduce the time that we need for the maintenance and optimization of the Database, as well as to avoid server capacity problems as the number of users continue to grow.

#MongoDB

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Matt Welke
Matt Welke
Software Developer at GroupBy Inc. | 1 upvotes 14.7K views
MongoDB Atlas
MongoDB Atlas

When creating small proofs of concept or personal projects with document data models, that require a lot of data storage but don't warrant paying for hosting, I use Atlas because of the 500 MB free tier and ease of setup.

Often paired with AWS Lambda or Google Cloud Functions. MongoDB Atlas

See more

MongoDB Atlas's Features

  • Global clusters for world-class applications. Support for 60+ cloud regions across AWS, Azure, & GCP.
  • Secure for sensitive data. Built-in security controls and features to meet your existing protocols and compliance standards.
  • Designed for developer productivity. Integrated tools to manipulate, visualize, and analyze your data. Execute code in real time in response to data changes.
  • Reliable for mission-critical workload. Highly available with distributed fault tolerance and backup options to meet your data recovery objectives.
  • Built for optimal performance. On-demand scaling, resource optimization tools, and real-time visibility into database performance.

MongoDB Atlas Alternatives & Comparisons

What are some alternatives to MongoDB Atlas?
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
MongoDB Compass
Visually explore your data. Run ad hoc queries in seconds. Interact with your data with full CRUD functionality. View and optimize your query performance.
MongoDB Cloud Manager
It is a hosted platform for managing MongoDB on the infrastructure of your choice. It saves you time, money, and helps you protect your customer experience by eliminating the guesswork from running MongoDB.
Azure Cosmos DB
Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.
Firebase
Firebase is a cloud service designed to power real-time, collaborative applications. Simply add the Firebase library to your application to gain access to a shared data structure; any changes you make to that data are automatically synchronized with the Firebase cloud and with other clients within milliseconds.
See all alternatives

MongoDB Atlas's Followers
355 developers follow MongoDB Atlas to keep up with related blogs and decisions.
Antony Prince
Ali Ben Mussa
Ben Cowden
Aza Miah
Eugene Lazorenko
Paul Liu
Denise Chen
Juan Jose Silup煤 Maza
bhairavi gupta
Oscar Xing Luo