Alternatives to Mediasoup logo

Alternatives to Mediasoup

Jitsi, Kurento, JavaScript, Git, and GitHub are the most popular alternatives and competitors to Mediasoup.
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What is Mediasoup and what are its top alternatives?

Mediasoup and its client side libraries provide a super low level API. They are intended to enable different use cases and scenarios, without any constraint or assumption. Some of these use cases are: Group video chat applications, One-to-many (or few-to-many) broadcasting applications in real-time, and RTP streaming.
Mediasoup is a tool in the Web and Video Conferencing category of a tech stack.
Mediasoup is an open source tool with 6K GitHub stars and 1.1K GitHub forks. Here’s a link to Mediasoup's open source repository on GitHub

Top Alternatives to Mediasoup

  • Jitsi
    Jitsi

    Jitsi (acquired by 8x8) is a set of open-source projects that allows you to easily build and deploy secure videoconferencing solutions. At the heart of Jitsi are Jitsi Videobridge and Jitsi Meet, which let you have conferences on the internet, while other projects in the community enable other features such as audio, dial-in, recording, and simulcasting. ...

  • Kurento
    Kurento

    It is a WebRTC media server and a set of client APIs making simple the development of advanced video applications for WWW and smartphone platforms. Media Server features include group communications, transcoding and more. ...

  • JavaScript
    JavaScript

    JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles. ...

  • Git
    Git

    Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency. ...

  • GitHub
    GitHub

    GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. ...

  • Python
    Python

    Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best. ...

  • jQuery
    jQuery

    jQuery is a cross-platform JavaScript library designed to simplify the client-side scripting of HTML. ...

  • Node.js
    Node.js

    Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices. ...

Mediasoup alternatives & related posts

Jitsi logo

Jitsi

249
719
93
Multi-platform open-source video conferencing
249
719
+ 1
93
PROS OF JITSI
  • 32
    Open Source
  • 20
    Entirely free conferencing
  • 19
    Unlimited time
  • 5
    Accessible from browser
  • 3
    Desktop, app and browser tab sharing
  • 3
    WebRTC standard
  • 2
    Secure & encrypted video conference
  • 2
    Great API to develop with
  • 2
    Live stream to youtube
  • 1
    Dial-In and Dial-Out via SIP
  • 1
    Full HD
  • 1
    FSB Approved
  • 1
    Share youtube videos in conference
  • 1
    Easy installation and good support
  • 0
    MCU
CONS OF JITSI
  • 7
    UnLimited time
  • 5
    No multiplatform
  • 1
    Great quality
  • 1
    Good support
  • 1
    Live conference statistics
  • 1
    Great features

related Jitsi posts

Shared insights
on
JitsiJitsiJavaScriptJavaScript

For weeks I have been researching to find an open source video conferencing platform that allows integration from native clients. I am working on a solution that would need to communicate from a native app via a windows dll (at least initially). Ultimately, I want any OS to talk to it natively. A lot of platforms provide the JavaScript interface (like Jitsi) but wrapping this in a windows dll is both complicated and has a huge footprint. What open source video conference servers are available that have native windows clients that can be packaged in a DLL?

See more
Shared insights
on
JitsiJitsiZoomZoom

A common issue with Zoom is the "half-duplex" operation, where only one person can speak at a time, and another person speaking will cause an interrupt and take control. Hence the infernal mute button is so needed. Does Jitsi allow for a "full-duplex" communication to occur? An example scenario is two people singing a duet, which is impossible on a Zoom call.

Many Thanks, Garry

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Kurento logo

Kurento

40
140
5
A WebRTC media server and a set of client APIs
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140
+ 1
5
PROS OF KURENTO
  • 5
    MCU
CONS OF KURENTO
    Be the first to leave a con

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    JavaScript logo

    JavaScript

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      Most Popular Language in the World
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      Powerful
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      For the good parts
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      Hard 彤
    CONS OF JAVASCRIPT
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      A constant moving target, too much churn
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      Horribly inconsistent
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      Javascript is the New PHP
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      Can be ugly
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      HORRIBLE DOCUMENTS, faulty code, repo has bugs

    related JavaScript posts

    Zach Holman

    Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.

    But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.

    But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.

    Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.

    See more
    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 11.2M views

    How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

    Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

    Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

    https://eng.uber.com/distributed-tracing/

    (GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

    Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

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    Git logo

    Git

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    • 1
      Doesn't scale for big data

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    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.9M views

    Our whole DevOps stack consists of the following tools:

    • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
    • Respectively Git as revision control system
    • SourceTree as Git GUI
    • Visual Studio Code as IDE
    • CircleCI for continuous integration (automatize development process)
    • Prettier / TSLint / ESLint as code linter
    • SonarQube as quality gate
    • Docker as container management (incl. Docker Compose for multi-container application management)
    • VirtualBox for operating system simulation tests
    • Kubernetes as cluster management for docker containers
    • Heroku for deploying in test environments
    • nginx as web server (preferably used as facade server in production environment)
    • SSLMate (using OpenSSL) for certificate management
    • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
    • PostgreSQL as preferred database system
    • Redis as preferred in-memory database/store (great for caching)

    The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

    • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
    • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
    • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
    • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
    • Scalability: All-in-one framework for distributed systems.
    • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
    See more
    Tymoteusz Paul
    Devops guy at X20X Development LTD · | 23 upvotes · 8.9M views

    Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

    It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

    I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

    We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

    If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

    The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

    Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

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    GitHub logo

    GitHub

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    related GitHub posts

    Johnny Bell

    I was building a personal project that I needed to store items in a real time database. I am more comfortable with my Frontend skills than my backend so I didn't want to spend time building out anything in Ruby or Go.

    I stumbled on Firebase by #Google, and it was really all I needed. It had realtime data, an area for storing file uploads and best of all for the amount of data I needed it was free!

    I built out my application using tools I was familiar with, React for the framework, Redux.js to manage my state across components, and styled-components for the styling.

    Now as this was a project I was just working on in my free time for fun I didn't really want to pay for hosting. I did some research and I found Netlify. I had actually seen them at #ReactRally the year before and deployed a Gatsby site to Netlify already.

    Netlify was very easy to setup and link to my GitHub account you select a repo and pretty much with very little configuration you have a live site that will deploy every time you push to master.

    With the selection of these tools I was able to build out my application, connect it to a realtime database, and deploy to a live environment all with $0 spent.

    If you're looking to build out a small app I suggest giving these tools a go as you can get your idea out into the real world for absolutely no cost.

    See more

    Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.

    Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!

    Check Out My Architecture: CLICK ME

    Check out the GitHub repo attached

    See more
    Python logo

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    • 4
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    • 3
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      Batteries included
    • 2
      Should START with this but not STICK with This
    • 2
      Powerful language for AI
    • 2
      Can understand easily who are new to programming
    • 2
      Flexible and easy
    • 2
      Good for hacking
    • 2
      A-to-Z
    • 2
      Because of Netflix
    • 2
      Only one way to do it
    • 2
      Better outcome
    • 1
      Sexy af
    • 1
      Slow
    • 1
      Securit
    • 0
      Ni
    • 0
      Powerful
    CONS OF PYTHON
    • 53
      Still divided between python 2 and python 3
    • 28
      Performance impact
    • 26
      Poor syntax for anonymous functions
    • 22
      GIL
    • 19
      Package management is a mess
    • 14
      Too imperative-oriented
    • 12
      Hard to understand
    • 12
      Dynamic typing
    • 12
      Very slow
    • 8
      Indentations matter a lot
    • 8
      Not everything is expression
    • 7
      Incredibly slow
    • 7
      Explicit self parameter in methods
    • 6
      Requires C functions for dynamic modules
    • 6
      Poor DSL capabilities
    • 6
      No anonymous functions
    • 5
      Fake object-oriented programming
    • 5
      Threading
    • 5
      The "lisp style" whitespaces
    • 5
      Official documentation is unclear.
    • 5
      Hard to obfuscate
    • 5
      Circular import
    • 4
      Lack of Syntax Sugar leads to "the pyramid of doom"
    • 4
      The benevolent-dictator-for-life quit
    • 4
      Not suitable for autocomplete
    • 2
      Meta classes
    • 1
      Training wheels (forced indentation)

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    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 11.2M views

    How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

    Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

    Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

    https://eng.uber.com/distributed-tracing/

    (GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

    Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

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    Nick Parsons
    Building cool things on the internet 🛠️ at Stream · | 35 upvotes · 4M views

    Winds 2.0 is an open source Podcast/RSS reader developed by Stream with a core goal to enable a wide range of developers to contribute.

    We chose JavaScript because nearly every developer knows or can, at the very least, read JavaScript. With ES6 and Node.js v10.x.x, it’s become a very capable language. Async/Await is powerful and easy to use (Async/Await vs Promises). Babel allows us to experiment with next-generation JavaScript (features that are not in the official JavaScript spec yet). Yarn allows us to consistently install packages quickly (and is filled with tons of new tricks)

    We’re using JavaScript for everything – both front and backend. Most of our team is experienced with Go and Python, so Node was not an obvious choice for this app.

    Sure... there will be haters who refuse to acknowledge that there is anything remotely positive about JavaScript (there are even rants on Hacker News about Node.js); however, without writing completely in JavaScript, we would not have seen the results we did.

    #FrameworksFullStack #Languages

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    jQuery logo

    jQuery

    190.7K
    67.3K
    6.6K
    The Write Less, Do More, JavaScript Library.
    190.7K
    67.3K
    + 1
    6.6K
    PROS OF JQUERY
    • 1.3K
      Cross-browser
    • 957
      Dom manipulation
    • 809
      Power
    • 660
      Open source
    • 610
      Plugins
    • 459
      Easy
    • 395
      Popular
    • 350
      Feature-rich
    • 281
      Html5
    • 227
      Light weight
    • 93
      Simple
    • 84
      Great community
    • 79
      CSS3 Compliant
    • 69
      Mobile friendly
    • 67
      Fast
    • 43
      Intuitive
    • 42
      Swiss Army knife for webdev
    • 35
      Huge Community
    • 11
      Easy to learn
    • 4
      Clean code
    • 3
      Because of Ajax request :)
    • 2
      Powerful
    • 2
      Nice
    • 2
      Just awesome
    • 2
      Used everywhere
    • 1
      Improves productivity
    • 1
      Javascript
    • 1
      Easy Setup
    • 1
      Open Source, Simple, Easy Setup
    • 1
      It Just Works
    • 1
      Industry acceptance
    • 1
      Allows great manipulation of HTML and CSS
    • 1
      Widely Used
    • 1
      I love jQuery
    CONS OF JQUERY
    • 6
      Large size
    • 5
      Sometimes inconsistent API
    • 5
      Encourages DOM as primary data source
    • 2
      Live events is overly complex feature

    related jQuery posts

    Kir Shatrov
    Engineering Lead at Shopify · | 22 upvotes · 2.1M views

    The client-side stack of Shopify Admin has been a long journey. It started with HTML templates, jQuery and Prototype. We moved to Batman.js, our in-house Single-Page-Application framework (SPA), in 2013. Then, we re-evaluated our approach and moved back to statically rendered HTML and vanilla JavaScript. As the front-end ecosystem matured, we felt that it was time to rethink our approach again. Last year, we started working on moving Shopify Admin to React and TypeScript.

    Many things have changed since the days of jQuery and Batman. JavaScript execution is much faster. We can easily render our apps on the server to do less work on the client, and the resources and tooling for developers are substantially better with React than we ever had with Batman.

    #FrameworksFullStack #Languages

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    Ganesa Vijayakumar
    Full Stack Coder | Technical Lead · | 19 upvotes · 4.9M views

    I'm planning to create a web application and also a mobile application to provide a very good shopping experience to the end customers. Shortly, my application will be aggregate the product details from difference sources and giving a clear picture to the user that when and where to buy that product with best in Quality and cost.

    I have planned to develop this in many milestones for adding N number of features and I have picked my first part to complete the core part (aggregate the product details from different sources).

    As per my work experience and knowledge, I have chosen the followings stacks to this mission.

    UI: I would like to develop this application using React, React Router and React Native since I'm a little bit familiar on this and also most importantly these will help on developing both web and mobile apps. In addition, I'm gonna use the stacks JavaScript, jQuery, jQuery UI, jQuery Mobile, Bootstrap wherever required.

    Service: I have planned to use Java as the main business layer language as I have 7+ years of experience on this I believe I can do better work using Java than other languages. In addition, I'm thinking to use the stacks Node.js.

    Database and ORM: I'm gonna pick MySQL as DB and Hibernate as ORM since I have a piece of good knowledge and also work experience on this combination.

    Search Engine: I need to deal with a large amount of product data and it's in-detailed info to provide enough details to end user at the same time I need to focus on the performance area too. so I have decided to use Solr as a search engine for product search and suggestions. In addition, I'm thinking to replace Solr by Elasticsearch once explored/reviewed enough about Elasticsearch.

    Host: As of now, my plan to complete the application with decent features first and deploy it in a free hosting environment like Docker and Heroku and then once it is stable then I have planned to use the AWS products Amazon S3, EC2, Amazon RDS and Amazon Route 53. I'm not sure about Microsoft Azure that what is the specialty in it than Heroku and Amazon EC2 Container Service. Anyhow, I will do explore these once again and pick the best suite one for my requirement once I reached this level.

    Build and Repositories: I have decided to choose Apache Maven and Git as these are my favorites and also so popular on respectively build and repositories.

    Additional Utilities :) - I would like to choose Codacy for code review as their Startup plan will be very helpful to this application. I'm already experienced with Google CheckStyle and SonarQube even I'm looking something on Codacy.

    Happy Coding! Suggestions are welcome! :)

    Thanks, Ganesa

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    Node.js logo

    Node.js

    186K
    157.8K
    8.5K
    A platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications
    186K
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    PROS OF NODE.JS
    • 1.4K
      Npm
    • 1.3K
      Javascript
    • 1.1K
      Great libraries
    • 1K
      High-performance
    • 805
      Open source
    • 486
      Great for apis
    • 477
      Asynchronous
    • 423
      Great community
    • 390
      Great for realtime apps
    • 296
      Great for command line utilities
    • 84
      Websockets
    • 83
      Node Modules
    • 69
      Uber Simple
    • 59
      Great modularity
    • 58
      Allows us to reuse code in the frontend
    • 42
      Easy to start
    • 35
      Great for Data Streaming
    • 32
      Realtime
    • 28
      Awesome
    • 25
      Non blocking IO
    • 18
      Can be used as a proxy
    • 17
      High performance, open source, scalable
    • 16
      Non-blocking and modular
    • 15
      Easy and Fun
    • 14
      Easy and powerful
    • 13
      Future of BackEnd
    • 13
      Same lang as AngularJS
    • 12
      Fullstack
    • 11
      Fast
    • 10
      Scalability
    • 10
      Cross platform
    • 9
      Simple
    • 8
      Mean Stack
    • 7
      Great for webapps
    • 7
      Easy concurrency
    • 6
      Typescript
    • 6
      Fast, simple code and async
    • 6
      React
    • 6
      Friendly
    • 5
      Control everything
    • 5
      Its amazingly fast and scalable
    • 5
      Easy to use and fast and goes well with JSONdb's
    • 5
      Scalable
    • 5
      Great speed
    • 5
      Fast development
    • 4
      It's fast
    • 4
      Easy to use
    • 4
      Isomorphic coolness
    • 3
      Great community
    • 3
      Not Python
    • 3
      Sooper easy for the Backend connectivity
    • 3
      TypeScript Support
    • 3
      Blazing fast
    • 3
      Performant and fast prototyping
    • 3
      Easy to learn
    • 3
      Easy
    • 3
      Scales, fast, simple, great community, npm, express
    • 3
      One language, end-to-end
    • 3
      Less boilerplate code
    • 2
      Npm i ape-updating
    • 2
      Event Driven
    • 2
      Lovely
    • 1
      Creat for apis
    • 0
      Node
    CONS OF NODE.JS
    • 46
      Bound to a single CPU
    • 45
      New framework every day
    • 40
      Lots of terrible examples on the internet
    • 33
      Asynchronous programming is the worst
    • 24
      Callback
    • 19
      Javascript
    • 11
      Dependency hell
    • 11
      Dependency based on GitHub
    • 10
      Low computational power
    • 7
      Very very Slow
    • 7
      Can block whole server easily
    • 7
      Callback functions may not fire on expected sequence
    • 4
      Breaking updates
    • 4
      Unstable
    • 3
      Unneeded over complication
    • 3
      No standard approach
    • 1
      Bad transitive dependency management
    • 1
      Can't read server session

    related Node.js posts

    Shared insights
    on
    Node.jsNode.jsGraphQLGraphQLMongoDBMongoDB

    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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    Nick Rockwell
    SVP, Engineering at Fastly · | 46 upvotes · 3.6M views

    When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?

    So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.

    React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.

    Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.

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