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What is 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 is a tool in the Databases category of a tech stack.
MongoDB is an open source tool with 17.1K GitHub stars and 4.3K GitHub forks. Here’s a link to MongoDB's open source repository on GitHub

Who uses MongoDB?

Companies
2975 companies reportedly use MongoDB in their tech stacks, including Uber, Lyft, and Codecademy.

Developers
13329 developers on StackShare have stated that they use MongoDB.

MongoDB Integrations

Datadog, Let's Encrypt, Mongoose, JSON, and MongoDB Atlas are some of the popular tools that integrate with MongoDB. Here's a list of all 95 tools that integrate with MongoDB.

Why developers like MongoDB?

Here’s a list of reasons why companies and developers use MongoDB
MongoDB Reviews

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

Node.js
Node.js
GraphQL
GraphQL
MongoDB
MongoDB

I just finished the very first version of my new hobby project: #MovieGeeks. It is a minimalist online movie catalog for you to save the movies you want to see and for rating the movies you already saw. This is just the beginning as I am planning to add more features on the lines of sharing and discovery

For the #BackEnd I decided to use Node.js , GraphQL and MongoDB:

  1. Node.js has a huge community so it will always be a safe choice in terms of libraries and finding solutions to problems you may have

  2. GraphQL because I needed to improve my skills with it and because I was never comfortable with the usual REST approach. I believe GraphQL is a better option as it feels more natural to write apis, it improves the development velocity, by definition it fixes the over-fetching and under-fetching problem that is so common on REST apis, and on top of that, the community is getting bigger and bigger.

  3. MongoDB was my choice for the database as I already have a lot of experience working on it and because, despite of some bad reputation it has acquired in the last months, I still believe it is a powerful database for at least a very long list of use cases such as the one I needed for my website

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Vaibhav Taunk
Vaibhav Taunk
Team Lead at Technovert · | 26 upvotes · 94.6K views
.NET Core
.NET Core
Angular CLI
Angular CLI
React
React
MongoDB
MongoDB
Flutter
Flutter
React Native
React Native
Postman
Postman
Markdown
Markdown
Visual Studio Code
Visual Studio Code

I am starting to become a full-stack developer, by choosing and learning .NET Core for API Development, Angular CLI / React for UI Development, MongoDB for database, as it a NoSQL DB and Flutter / React Native for Mobile App Development. Using Postman, Markdown and Visual Studio Code for development.

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Jeyabalaji Subramanian
Jeyabalaji Subramanian
CTO at FundsCorner · | 24 upvotes · 341K views
atFundsCornerFundsCorner
MongoDB
MongoDB
PostgreSQL
PostgreSQL
MongoDB Stitch
MongoDB Stitch
Node.js
Node.js
Amazon SQS
Amazon SQS
Python
Python
SQLAlchemy
SQLAlchemy
AWS Lambda
AWS Lambda
Zappa
Zappa

Recently we were looking at a few robust and cost-effective ways of replicating the data that resides in our production MongoDB to a PostgreSQL database for data warehousing and business intelligence.

We set ourselves the following criteria for the optimal tool that would do this job: - The data replication must be near real-time, yet it should NOT impact the production database - The data replication must be horizontally scalable (based on the load), asynchronous & crash-resilient

Based on the above criteria, we selected the following tools to perform the end to end data replication:

We chose MongoDB Stitch for picking up the changes in the source database. It is the serverless platform from MongoDB. One of the services offered by MongoDB Stitch is Stitch Triggers. Using stitch triggers, you can execute a serverless function (in Node.js) in real time in response to changes in the database. When there are a lot of database changes, Stitch automatically "feeds forward" these changes through an asynchronous queue.

We chose Amazon SQS as the pipe / message backbone for communicating the changes from MongoDB to our own replication service. Interestingly enough, MongoDB stitch offers integration with AWS services.

In the Node.js function, we wrote minimal functionality to communicate the database changes (insert / update / delete / replace) to Amazon SQS.

Next we wrote a minimal micro-service in Python to listen to the message events on SQS, pickup the data payload & mirror the DB changes on to the target Data warehouse. We implemented source data to target data translation by modelling target table structures through SQLAlchemy . We deployed this micro-service as AWS Lambda with Zappa. With Zappa, deploying your services as event-driven & horizontally scalable Lambda service is dumb-easy.

In the end, we got to implement a highly scalable near realtime Change Data Replication service that "works" and deployed to production in a matter of few days!

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Robert Zuber
Robert Zuber
CTO at CircleCI · | 22 upvotes · 212.7K views
atCircleCICircleCI
MongoDB
MongoDB
PostgreSQL
PostgreSQL
Redis
Redis
GitHub
GitHub
Amazon S3
Amazon S3

We use MongoDB as our primary #datastore. Mongo's approach to replica sets enables some fantastic patterns for operations like maintenance, backups, and #ETL.

As we pull #microservices from our #monolith, we are taking the opportunity to build them with their own datastores using PostgreSQL. We also use Redis to cache data we’d never store permanently, and to rate-limit our requests to partners’ APIs (like GitHub).

When we’re dealing with large blobs of immutable data (logs, artifacts, and test results), we store them in Amazon S3. We handle any side-effects of S3’s eventual consistency model within our own code. This ensures that we deal with user requests correctly while writes are in process.

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Greg SwissDev
Greg SwissDev
Founder at SwissDev Jobs · | 20 upvotes · 49.3K views
atSwissDev JobsSwissDev Jobs
Node.js
Node.js
React
React
MongoDB
MongoDB

When building https://swissdevjobs.ch in 2018 we decided to go with a very simple stack with Node.js React and MongoDB. The decision was mostly because we already had experience with this stack and needed something to build a quick prototype.

Fast forward 1 year and in August 2019 we have over 12'000 monthly users and survived the traffic spikes from Hacker News and Product Hunt. It also proved to be very suited well for easy deployments and adding new features, including a public API.

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Nicolas Apx
Nicolas Apx
CEO - FullStack Javascript at Apx Development Limited · | 14 upvotes · 21.4K views
atAPX DevelopmentAPX Development
Python
Python
Node.js
Node.js
MongoDB
MongoDB
PostgreSQL
PostgreSQL

I am planning on building a micro-service eCommerce back-end to be easy to reuse in any project as we need. I would like to use both Python and Node.js and MongoDB & PostgreSQL , in your opinion which one would best suited for the following services:

  • Users-service
  • Products-service
  • Auth-service
  • Inventory-service
  • Order-service
  • Payment-service
  • Sku-service
  • And more not yet defined....

Thanks

Nicolas

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MongoDB's Features

  • Flexible data model, expressive query language, secondary indexes, replication, auto-sharding, in-place updates, aggregation, GridFS

MongoDB Alternatives & Comparisons

What are some alternatives to MongoDB?
Amazon DynamoDB
With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
Couchbase
Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
PostgreSQL
PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
See all alternatives

MongoDB's Followers
13421 developers follow MongoDB to keep up with related blogs and decisions.
Sascha Perkowski
Nicholas Leisen
Dustin Armstrong
Aendenne X
Zaraki Kenpachi
mohamed_jebali
Vasiliy Trofimov
Lalit Nayyar
Anbuselvan Samiyappan
Prashant Vithani