ExpressJS vs Node.js: What are the differences?
ExpressJS belongs to "Microframeworks (Backend)" category of the tech stack, while Node.js can be primarily classified under "Frameworks (Full Stack)".
ExpressJS and Node.js are both open source tools. ExpressJS with 44.6K GitHub stars and 7.48K forks on GitHub appears to be more popular than Node.js with 35.5K GitHub stars and 7.78K GitHub forks.
According to the StackShare community, Node.js has a broader approval, being mentioned in 4104 company stacks & 4042 developers stacks; compared to ExpressJS, which is listed in 854 company stacks and 790 developer stacks.
What is ExpressJS?
What is Node.js?
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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.
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
I think next step could be to use Koa but I am not sure.
Node.js powers our Cloud App Servers and performs the server-side logic required to provide useful business operations like those in Approvals for Confluence. Our Node.js Apps are written in TypeScript and use the ExpressJS framework to serve requests, along with other libraries to manage data storage and security. In production these Node.js processes are run in Docker containers, split across multiple Cluster nodes using the Amazon EC2 Container Service.
I use Socket.IO because the application has 2 frontend clients, which need to communicate in real-time. The backend-server handles the communication between these two clients via websockets. Socket.io is very easy to set up in Node.js and ExpressJS.
In the research project, the 1st client shows panoramic videos in a so called cave system (it is the VR setup of our research lab, which consists of three big screens, which are specially arranged, so the user experience the videos more immersive), the 2nd client controls the videos/locations of the 1st client.
When we started thinking about technology options for our own Design System, we wanted to focus on two primary goals
- Build a design system site using design system components - a living prototype
- Explore new ways of working to position our technical capabilities for the future
We have a small team of developers responsible for the initial build so we knew that we couldn’t spend too much time maintaining infrastructure on the Backend. We also wanted freedom to make decisions on the Frontend with the ability to adapt over time.
For this first iteration we decided to use Node.js, React, and Next.js. Content will be managed via headless CMS in prismic.io.
- Next.js so that we can run React serverside without worrying about server code.
- prismic.io so that our content is accessible via API and our frontend is fully independent.
Possible pros for Python / Django: - easy syntax, easier to learn for me as a beginner - fast development, earlier release - libraries for mathematical and scientific computation
Which software would you use in my case? Are my arguments for Python/NodeJS right? Which kind of database would you use?
Thank you for your answer!
This is the third Stack Decision of this series. You can read the last one to catch up (link below).
Josh is a machine. He cranked out the rewrite of the site and as well as the Amazon S3 syncing/permissions/
content-type scripts in less than a week (with a full time job + 2 small kids at the time). The new site had/has a section where you could try out all of the Bootswatch themes on our site and while it might sound silly, it showed me that he goes above and beyond and I totally lucked out.
Anyway, Josh decided to go with Node.js, ExpressJS, Jade (now called Pug), and configs with #yaml, all things I have read about but never used in production. I quickly found out Josh was a Vim user (still is), because every Jade file he worked on had
//- vim: ft=jade sw=4 sts=4 et: at the bottom.
Everything was running smoothly, I was encouraged by David (co-founder from part 1) to take a vacation. I took him up on that. Unfortunately, my timing couldn’t have been worse. More on that in part 4.
AMA below 👇
Recently I have been working on an open source stack to help people consolidate their personal health data in a single database so that AI and analytics apps can be run against it to find personalized treatments. We chose to go with a #containerized approach leveraging Docker #containers with a local development environment setup with Docker Compose and nginx for container routing. For the production environment we chose to pull code from GitHub and build/push images using Jenkins and using Kubernetes to deploy to Amazon EC2.
We also implemented a dashboard app to handle user authentication/authorization, as well as a custom SSO server that runs on Heroku which allows experts to easily visit more than one instance without having to login repeatedly. The #Backend was implemented using my favorite #Stack which consists of FeathersJS on top of Node.js and ExpressJS with PostgreSQL as the main database. The #Frontend was implemented using React, Redux.js, Semantic UI React and the FeathersJS client. Though testing was light on this project, we chose to use AVA as well as ESLint to keep the codebase clean and consistent.
Mixmax was originally built using Meteor as a single monolithic app. As more users began to onboard, we started noticing scaling issues, and so we broke out our first microservice: our Compose service, for writing emails and Sequences, was born as a Node.js service. Soon after that, we broke out all recipient searching and storage functionality to another Node.js microservice, our Contacts service. This practice of breaking out microservices in order to help our system more appropriately scale, by being more explicit about each microservice’s responsibilities, continued as we broke out numerous more microservices.
As Mixmax began to scale super quickly, with more and more customers joining the platform, we started to see that the Meteor app was still having a lot of trouble scaling due to how it tried to provide its reactivity layer. To be honest, this led to a brutal summer of playing Galaxy container whack-a-mole as containers would saturate their CPU and become unresponsive. I’ll never forget hacking away at building a new microservice to relieve the load on the system so that we’d stop getting paged every 30-40 minutes. Luckily, we’ve never had to do that again! After stabilizing the system, we had to build out two more microservices to provide the necessary reactivity and authentication layers as we rebuilt our Meteor app from the ground up in Node.js. This also had the added benefit of being able to deploy the entire application in the same AWS VPCs. Thankfully, AWS had also released their ALB product so that we didn’t have to build and maintain our own websocket layer in Amazon EC2. All of our microservices, except for one special Go one, are now in Node with an nginx frontend on each instance, all behind AWS Elastic Load Balancing (ELB) or ALBs running in AWS Elastic Beanstalk.
I'm building most projects using: Server: either Fastify (all projects going forward) or ExpressJS on Node.js (existing, previously) on the server side, and Client app: either Vuetify (currently) or Quasar Framework (going forward) on Vue.js with vuex on Electron for the UI to deliver both web-based and desktop applications for multiple platforms.
The direct support for Android and iOS in Quasar Framework will make it my go-to client UI platform for any new client-side or web work. On the server, I'll probably use Fastly for all my server work, unless I get into Go more in the future.
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
At IT Minds we create customized internal or #B2B web and mobile apps. I have a go to stack that I pitch to our customers consisting of 3 core areas. 1) A data core #backend . 2) A micro #serverless #backend. 3) A user client #frontend.
For the Data Core I create a backend using TypeScript Node.js and with TypeORM connecting to a PostgreSQL Exposing an action based api with Apollo GraphQL
For the micro serverless backend, which purpose is verification for authentication, autorization, logins and the likes. It is created with Next.js api pages. Using MongoDB to store essential information, caching etc.
Finally the frontend is built with React using Next.js , TypeScript and @Apollo. We create the frontend as a PWA and have a AMP landing page by default.
I use LoopBack because it is: * It is truly and Unbelievably Extensible * it is default integrated with OpenAPI (Swagger) Spec Driven REST API * I write lesser codes, because most of the user stories have been covered using the code generation * It's documentation is more compact and well detailed than ExpressJS * It is very easy to learn, hence you can build a basic Rest API App in minutes * It has built in NPM packages required to build my Rest API which saves me time on installation and configuration * The Datasource/Service/Controller concept is just Brilliant (that's mostly all you need to get your app speaking with an External API services) * The support for SOAP and Rest API services is amazing!
I have benchmarked Node.js and other popular frameworks using a real life application example. You can find the results here: https://email@example.com/web-rest-api-benchmark-on-a-real-life-application-ebb743a5d7a3
We decided to move the provisioning process to an API-driven process, and had to decide among a few implementation languages:
- Go, the server-side language from Google
We built prototypes in both languages, and decided on NodeJS:
- NodeJS is asynchronous-by-default, which suited the problem domain. Provisioning is more like “start the job, let me know when you’re done” than a traditional C-style program that’s CPU-bound and needs low-level efficiency.
- NodeJS acts as an HTTP-based service, so exposing the API was trivial
Getting into the headspace and internalizing the assumptions of a tool helps pick the right one. NodeJS assumes services will be non-blocking/event-driven and HTTP-accessible, which snapped into our scenario perfectly. The new NodeJS architecture resulted in a staggering 95% reduction in processing time: requests went from 7.5 seconds to under a second.
The server side of Trello is built in Node.js. We knew we wanted instant propagation of updates, which meant that we needed to be able to hold a lot of open connections, so an event-driven, non-blocking server seemed like a good choice. Node also turned out to be an amazing prototyping tool for a single-page app. The prototype version of the Trello server was really just a library of functions that operated on arrays of Models in the memory of a single Node.js process, and the client simply invoked those functions through a very thin wrapper over a WebSocket. This was a very fast way for us to get started trying things out with Trello and making sure that the design was headed in the right direction. We used the prototype version to manage the development of Trello and other internal projects at Fog Creek.
All backend code is done in node.js
We have a SOA for our systems. It isn't quite Microservices jsut yet, but it does provide domain encapsulation for our systems allowing the leaderboards to fail without affecting the login or education content.
We've written a few internal modules including a very simple api framework.
I don't know how well this will scale if/when I have hundreds of people connected simultaneously, but I suspect that when that time comes, it may be just a matter of increasing the hardware.
Used node.js server as backend. Interacts with MongoDB using MongoSkin package which is a wrapper for the MongoDB node.js driver. It uses express for routing and cors package for enabling cors and eyes package for enhancing readability of logs. Also I use nodemon which takes away the effort to restart the server after making changes.
Express.js is the workhorse of the Cloudcraft.co backend. It's not the most exciting part of a stack, but it works, is very well documented, and you can find a plugin for almost everything you could possibly want. We also carefully evaluated Koa.js, but decided not to go down this route: fewer plugins, less documentation & answers online. I'm also not personally convinced by the generators yield syntax at all. ES7 async functions looks like a much better bet, and with Promises and Babel I can have that already today.
I use express.js for nightly.zerotoherojs.com and dojo.zerotoherojs.com web apps.
Express is well-known, lightweight, works out-of-the-box, has great middleware support and has minimal learning curve.
It is the best framework to start developing a general Node.js web app.
I'm fluent in ExpressJS, but over the past two years I have moved to HapiJS. Similar results, but I find Hapi to be more full-featured towards my app, api and service needs. I can operate confidently in both.
PrometheanTV utilizes the ExpressJS web application framework to deploy various web applications and services including the Broadcast Center Tool, our video embed service, and our REST API.