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Node.js
Node.js

37.1K
31K
+ 1
8K
Play
Play

563
304
+ 1
460
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Node.js vs Play: What are the differences?

Developers describe Node.js as "A platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications". 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. On the other hand, Play is detailed as "The High Velocity Web Framework For Java and Scala". Play Framework makes it easy to build web applications with Java & Scala. Play is based on a lightweight, stateless, web-friendly architecture. Built on Akka, Play provides predictable and minimal resource consumption (CPU, memory, threads) for highly-scalable applications.

Node.js and Play belong to "Frameworks (Full Stack)" category of the tech stack.

"Npm", "Javascript" and "Great libraries" are the key factors why developers consider Node.js; whereas "Scala", "Web-friendly architecture" and "Built on akka" are the primary reasons why Play is favored.

Node.js and Play are both open source tools. Node.js with 35.5K GitHub stars and 7.78K forks on GitHub appears to be more popular than Play with 11.2K GitHub stars and 3.75K GitHub forks.

According to the StackShare community, Node.js has a broader approval, being mentioned in 4055 company stacks & 3897 developers stacks; compared to Play, which is listed in 111 company stacks and 46 developer stacks.

What is 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.

What is Play?

Play Framework makes it easy to build web applications with Java & Scala. Play is based on a lightweight, stateless, web-friendly architecture. Built on Akka, Play provides predictable and minimal resource consumption (CPU, memory, threads) for highly-scalable applications.
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What are some alternatives to Node.js and Play?
AngularJS
AngularJS lets you write client-side web applications as if you had a smarter browser. It lets you use good old HTML (or HAML, Jade and friends!) as your template language and lets you extend HTML’s syntax to express your application’s components clearly and succinctly. It automatically synchronizes data from your UI (view) with your JavaScript objects (model) through 2-way data binding.
PHP
Fast, flexible and pragmatic, PHP powers everything from your blog to the most popular websites in the world.
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.
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.
React
Lots of people use React as the V in MVC. Since React makes no assumptions about the rest of your technology stack, it's easy to try it out on a small feature in an existing project.
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Decisions about Node.js and Play
Sparker73
Sparker73
Frontend Developer · | 7 upvotes · 23.1K views
Node.js
Node.js
JavaScript
JavaScript
.NET
.NET
PHP
PHP

Node.js is my choice because it uses very few resources to run and it is capable to handle tons of connections simultaneously. Most developers already know JavaScript, the evolution of ECMAScript is immediately reflected to Node.js and all you have to do is update your Server's Node.js version without time and effort. Thousands of improvements that makes it very powerful especially in asynchronous programming. The web is full of courses, dev communities, free sample code, plunkers and many knowledge sources on Node.js that facilitates the learning curve. What else we can ask from a legendary language that is still evolving? I am learning Node.js by developing a simple REST WebAPI and using it as a playground to test situations in which the main objective is to challenge Node.js and compare results and performance with .NET implementations and certain well known fast PHP implementations. Until now the results are astonishing. Summarizing: Node.js for backend is so far (in my opinion) the most recommended solution to get positive achievements in size, speed, power, concurrency, scalability, deployment and running costs.

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Antonio Sanchez
Antonio Sanchez
CEO at Kokoen GmbH · | 13 upvotes · 211K views
atKokoen GmbHKokoen GmbH
PHP
PHP
Laravel
Laravel
MySQL
MySQL
Go
Go
MongoDB
MongoDB
JavaScript
JavaScript
Node.js
Node.js
ExpressJS
ExpressJS

Back at the start of 2017, we decided to create a web-based tool for the SEO OnPage analysis of our clients' websites. We had over 2.000 websites to analyze, so we had to perform thousands of requests to get every single page from those websites, process the information and save the big amounts of data somewhere.

Very soon we realized that the initial chosen script language and database, PHP, Laravel and MySQL, was not going to be able to cope efficiently with such a task.

By that time, we were doing some experiments for other projects with a language we had recently get to know, Go , so we decided to get a try and code the crawler using it. It was fantastic, we could process much more data with way less CPU power and in less time. By using the concurrency abilites that the language has to offers, we could also do more Http requests in less time.

Unfortunately, I have no comparison numbers to show about the performance differences between Go and PHP since the difference was so clear from the beginning and that we didn't feel the need to do further comparison tests nor document it. We just switched fully to Go.

There was still a problem: despite the big amount of Data we were generating, MySQL was performing very well, but as we were adding more and more features to the software and with those features more and more different type of data to save, it was a nightmare for the database architects to structure everything correctly on the database, so it was clear what we had to do next: switch to a NoSQL database. So we switched to MongoDB, and it was also fantastic: we were expending almost zero time in thinking how to structure the Database and the performance also seemed to be better, but again, I have no comparison numbers to show due to the lack of time.

We also decided to switch the website from PHP and Laravel to JavaScript and Node.js and ExpressJS since working with the JSON Data that we were saving now in the Database would be easier.

As of now, we don't only use the tool intern but we also opened it for everyone to use for free: https://tool-seo.com

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Zarema Khalilova
Zarema Khalilova
Frontend Team Lead at Uploadcare · | 8 upvotes · 62.9K views
atUploadcareUploadcare
Django
Django
Node.js
Node.js
React
React
Gatsby
Gatsby
Netlify
Netlify
#Frontend
#StaticSiteGenerators
#StaticWebHosting

Since 2011 our frontend was in Django monolith. However, in 2016 we decide to separate #Frontend from Django for independent development and created the custom isomorphic app based on Node.js and React. Now we realized that not need all abilities of the server, and it is sufficient to generate a static site. Gatsby is suitable for our purposes. We can generate HTML from markdown and React views very simply. So, we are updating our frontend to Gatsby now, and maybe we will use Netlify for deployment soon. This will speed up the delivery of new features to production.

#StaticSiteGenerators #StaticWebHosting

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Russel Werner
Russel Werner
Lead Engineer at StackShare · | 21 upvotes · 503.4K views
atStackShareStackShare
React
React
Glamorous
Glamorous
Apollo
Apollo
Node.js
Node.js
Rails
Rails
Heroku
Heroku
GitHub
GitHub
Amazon S3
Amazon S3
Amazon CloudFront
Amazon CloudFront
Webpack
Webpack
CircleCI
CircleCI
Redis
Redis
#StackDecisionsLaunch
#SSR
#Microservices
#FrontEndRepoSplit

StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.

Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!

#StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit

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Julien DeFrance
Julien DeFrance
Principal Software Engineer at Tophatter · | 16 upvotes · 1.1M views
atSmartZipSmartZip
Rails
Rails
Rails API
Rails API
AWS Elastic Beanstalk
AWS Elastic Beanstalk
Capistrano
Capistrano
Docker
Docker
Amazon S3
Amazon S3
Amazon RDS
Amazon RDS
MySQL
MySQL
Amazon RDS for Aurora
Amazon RDS for Aurora
Amazon ElastiCache
Amazon ElastiCache
Memcached
Memcached
Amazon CloudFront
Amazon CloudFront
Segment
Segment
Zapier
Zapier
Amazon Redshift
Amazon Redshift
Amazon Quicksight
Amazon Quicksight
Superset
Superset
Elasticsearch
Elasticsearch
Amazon Elasticsearch Service
Amazon Elasticsearch Service
New Relic
New Relic
AWS Lambda
AWS Lambda
Node.js
Node.js
Ruby
Ruby
Amazon DynamoDB
Amazon DynamoDB
Algolia
Algolia

Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS