What is Deno and what are its top alternatives?
Top Alternatives to Deno
- 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. ...
- Golang
Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language. ...
- Rust
Rust is a systems programming language that combines strong compile-time correctness guarantees with fast performance. It improves upon the ideas of other systems languages like C++ by providing guaranteed memory safety (no crashes, no data races) and complete control over the lifecycle of memory. ...
- 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. ...
- npm
npm is the command-line interface to the npm ecosystem. It is battle-tested, surprisingly flexible, and used by hundreds of thousands of JavaScript developers every day. ...
- Modernizr
It’s a collection of superfast tests or detects as we like to call them which run as your web page loads, then you can use the results to tailor the experience to the user. It tells you what HTML, CSS and JavaScript features the user’s browser has to offer. ...
- Modernizr
It’s a collection of superfast tests or detects as we like to call them which run as your web page loads, then you can use the results to tailor the experience to the user. It tells you what HTML, CSS and JavaScript features the user’s browser has to offer. ...
- Lodash
A JavaScript utility library delivering consistency, modularity, performance, & extras. It provides utility functions for common programming tasks using the functional programming paradigm. ...
Deno alternatives & related posts
Node.js
- Npm1.4K
- Javascript1.3K
- Great libraries1.1K
- High-performance1K
- Open source802
- Great for apis485
- Asynchronous475
- Great community421
- Great for realtime apps390
- Great for command line utilities296
- Websockets82
- Node Modules82
- Uber Simple69
- Great modularity59
- Allows us to reuse code in the frontend58
- Easy to start42
- Great for Data Streaming35
- Realtime32
- Awesome28
- Non blocking IO25
- Can be used as a proxy18
- High performance, open source, scalable17
- Non-blocking and modular16
- Easy and Fun15
- Easy and powerful14
- Future of BackEnd13
- Same lang as AngularJS13
- Fullstack12
- Fast11
- Cross platform10
- Scalability10
- Simple9
- Mean Stack8
- Great for webapps7
- Easy concurrency7
- React6
- Typescript6
- Fast, simple code and async6
- Friendly6
- Fast development5
- Easy to use and fast and goes well with JSONdb's5
- Its amazingly fast and scalable5
- Scalable5
- Great speed5
- Control everything5
- Easy to use4
- It's fast4
- Isomorphic coolness4
- Great community3
- Scales, fast, simple, great community, npm, express3
- TypeScript Support3
- Sooper easy for the Backend connectivity3
- Not Python3
- One language, end-to-end3
- Easy3
- Easy to learn3
- Less boilerplate code3
- Performant and fast prototyping3
- Blazing fast3
- Event Driven2
- Lovely2
- Npm i ape-updating2
- Creat for apis1
- Node0
- Bound to a single CPU46
- New framework every day44
- Lots of terrible examples on the internet38
- Asynchronous programming is the worst31
- Callback23
- Javascript18
- Dependency based on GitHub11
- Dependency hell11
- Low computational power10
- Very very Slow7
- Can block whole server easily7
- Callback functions may not fire on expected sequence6
- Unneeded over complication3
- Unstable3
- Breaking updates3
- No standard approach2
- Bad transitive dependency management1
- Can't read server session1
related Node.js posts
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.
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
Golang
- High-performance538
- Simple, minimal syntax392
- Fun to write359
- Easy concurrency support via goroutines299
- Fast compilation times271
- Goroutines193
- Statically linked binaries that are simple to deploy179
- Simple compile build/run procedures150
- Backed by google136
- Great community134
- Garbage collection built-in52
- Built-in Testing45
- Excellent tools - gofmt, godoc etc43
- Elegant and concise like Python, fast like C39
- Awesome to Develop37
- Used for Docker26
- Flexible interface system25
- Deploy as executable24
- Great concurrency pattern24
- Open-source Integration20
- Easy to read17
- Fun to write and so many feature out of the box17
- Go is God16
- Its Simple and Heavy duty14
- Powerful and simple14
- Easy to deploy14
- Best language for concurrency13
- Concurrency12
- Rich standard library11
- Safe GOTOs11
- Clean code, high performance10
- Easy setup10
- Simplicity, Concurrency, Performance9
- High performance9
- Hassle free deployment8
- Single binary avoids library dependency issues8
- Simple, powerful, and great performance7
- Cross compiling7
- Used by Giants of the industry7
- Gofmt6
- Garbage Collection6
- Very sophisticated syntax5
- Excellent tooling5
- WYSIWYG5
- Kubernetes written on Go4
- Widely used4
- Keep it simple and stupid4
- No generics2
- Looks not fancy, but promoting pragmatic idioms1
- Operator goto1
- You waste time in plumbing code catching errors41
- Verbose25
- Packages and their path dependencies are braindead23
- Dependency management when working on multiple projects15
- Google's documentations aren't beginer friendly15
- Automatic garbage collection overheads10
- Uncommon syntax8
- Type system is lacking (no generics, etc)6
- Collection framework is lacking (list, set, map)3
- Best programming language2
related Golang posts
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
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
- Guaranteed memory safety140
- Fast127
- Open source85
- Minimal runtime75
- Pattern matching70
- Type inference62
- Concurrent56
- Algebraic data types56
- Efficient C bindings46
- Practical43
- Best advances in languages in 20 years37
- Safe, fast, easy + friendly community31
- Fix for C/C++30
- Stablity24
- Zero-cost abstractions24
- Closures23
- Extensive compiler checks20
- Great community19
- No NULL type18
- Async/await16
- Completely cross platform: Windows, Linux, Android15
- No Garbage Collection14
- High-performance14
- Great documentations13
- Super fast12
- Generics12
- High performance12
- Fearless concurrency11
- Guaranteed thread data race safety11
- Safety no runtime crashes11
- Macros10
- Helpful compiler10
- Compiler can generate Webassembly10
- Prevents data races9
- Easy Deployment9
- RLS provides great IDE support9
- Painless dependency management8
- Real multithreading7
- Good package management5
- Support on Other Languages5
- Hard to learn26
- Ownership learning curve23
- Unfriendly, verbose syntax11
- Variable shadowing4
- High size of builded executable4
- Many type operations make it difficult to follow4
- No jobs3
related Rust posts
Hello!
I'm a developer for over 9 years, and most of this time I've been working with C# and it is paying my bills until nowadays. But I'm seeking to learn other languages and expand the possibilities for the next years.
Now the question... I know Ruby is far from dead but is it still worth investing time in learning it? Or would be better to take Python, Golang, or even Rust? Or maybe another language.
Thanks in advance.
Sentry's event processing pipeline, which is responsible for handling all of the ingested event data that makes it through to our offline task processing, is written primarily in Python.
For particularly intense code paths, like our source map processing pipeline, we have begun re-writing those bits in Rust. Rust’s lack of garbage collection makes it a particularly convenient language for embedding in Python. It allows us to easily build a Python extension where all memory is managed from the Python side (if the Python wrapper gets collected by the Python GC we clean up the Rust object as well).
Python
- Great libraries1.2K
- Readable code953
- Beautiful code838
- Rapid development782
- Large community686
- Open source429
- Elegant388
- Great community280
- Object oriented271
- Dynamic typing216
- Great standard library76
- Very fast57
- Functional programming52
- Easy to learn45
- Scientific computing44
- Great documentation34
- Matlab alternative27
- Easy to read26
- Productivity26
- Simple is better than complex22
- It's the way I think19
- Imperative18
- Free17
- Very programmer and non-programmer friendly16
- Powerfull language15
- Machine learning support15
- Powerful14
- Fast and simple14
- Scripting13
- Explicit is better than implicit10
- Clear and easy and powerfull9
- Unlimited power9
- Ease of development9
- Import antigravity8
- Print "life is short, use python"7
- It's lean and fun to code7
- Now is better than never6
- Great for tooling6
- Flat is better than nested6
- Python has great libraries for data processing6
- Although practicality beats purity6
- I love snakes6
- High Documented language6
- There should be one-- and preferably only one --obvious6
- Fast coding and good for competitions6
- Rapid Prototyping5
- Readability counts5
- Plotting4
- Web scraping4
- CG industry needs4
- Great for analytics4
- Socially engaged community4
- Lists, tuples, dictionaries4
- Complex is better than complicated4
- Multiple Inheritence4
- Beautiful is better than ugly4
- Simple and easy to learn3
- Generators3
- Easy to learn and use3
- Many types of collections3
- No cruft3
- List comprehensions3
- Pip install everything3
- Special cases aren't special enough to break the rules3
- If the implementation is hard to explain, it's a bad id3
- If the implementation is easy to explain, it may be a g3
- Easy to setup and run smooth3
- Import this3
- Shitty2
- Flexible and easy2
- It is Very easy , simple and will you be love programmi2
- Batteries included2
- Can understand easily who are new to programming2
- Powerful language for AI2
- Should START with this but not STICK with This2
- A-to-Z2
- Because of Netflix2
- Only one way to do it2
- Better outcome2
- Good for hacking2
- Powerful0
- Still divided between python 2 and python 351
- Performance impact28
- Poor syntax for anonymous functions26
- GIL21
- Package management is a mess19
- Too imperative-oriented14
- Hard to understand12
- Dynamic typing12
- Very slow11
- Not everything is expression8
- Indentations matter a lot7
- Explicit self parameter in methods7
- Incredibly slow7
- Requires C functions for dynamic modules6
- Poor DSL capabilities6
- No anonymous functions6
- Official documentation is unclear.5
- The "lisp style" whitespaces5
- Fake object-oriented programming5
- Hard to obfuscate5
- Threading5
- Circular import4
- The benevolent-dictator-for-life quit4
- Lack of Syntax Sugar leads to "the pyramid of doom"4
- Not suitable for autocomplete4
- Meta classes2
- Training wheels (forced indentation)1
related Python posts
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
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
- Best package management system for javascript647
- Open-source382
- Great community327
- More packages than rubygems, pypi, or packagist148
- Nice people matter112
- Audit feature6
- As fast as yarn but really free of facebook5
- Good following4
- Super fast1
- Stability1
- Problems with lockfiles5
- Bad at package versioning and being deterministic5
- Node-gyp takes forever3
- Super slow1
related npm posts
Our whole Node.js backend stack consists of the following tools:
- Lerna as a tool for multi package and multi repository management
- npm as package manager
- NestJS as Node.js framework
- TypeScript as programming language
- ExpressJS as web server
- Swagger UI for visualizing and interacting with the API’s resources
- Postman as a tool for API development
- TypeORM as object relational mapping layer
- JSON Web Token for access token management
The main reason we have chosen Node.js over PHP is related to the following artifacts:
- Made for the web and widely in use: Node.js is a software platform for developing server-side network services. Well-known projects that rely on Node.js include the blogging software Ghost, the project management tool Trello and the operating system WebOS. Node.js requires the JavaScript runtime environment V8, which was specially developed by Google for the popular Chrome browser. This guarantees a very resource-saving architecture, which qualifies Node.js especially for the operation of a web server. Ryan Dahl, the developer of Node.js, released the first stable version on May 27, 2009. He developed Node.js out of dissatisfaction with the possibilities that JavaScript offered at the time. The basic functionality of Node.js has been mapped with JavaScript since the first version, which can be expanded with a large number of different modules. The current package managers (npm or Yarn) for Node.js know more than 1,000,000 of these modules.
- Fast server-side solutions: Node.js adopts the JavaScript "event-loop" to create non-blocking I/O applications that conveniently serve simultaneous events. With the standard available asynchronous processing within JavaScript/TypeScript, highly scalable, server-side solutions can be realized. The efficient use of the CPU and the RAM is maximized and more simultaneous requests can be processed than with conventional multi-thread servers.
- A language along the entire stack: Widely used frameworks such as React or AngularJS or Vue.js, which we prefer, are written in JavaScript/TypeScript. If Node.js is now used on the server side, you can use all the advantages of a uniform script language throughout the entire application development. The same language in the back- and frontend simplifies the maintenance of the application and also the coordination within the development team.
- Flexibility: Node.js sets very few strict dependencies, rules and guidelines and thus grants a high degree of flexibility in application development. There are no strict conventions so that the appropriate architecture, design structures, modules and features can be freely selected for the development.
So when starting a new project you generally have your go to tools to get your site up and running locally, and some scripts to build out a production version of your site. Create React App is great for that, however for my projects I feel as though there is to much bloat in Create React App and if I use it, then I'm tied to React, which I love but if I want to switch it up to Vue or something I want that flexibility.
So to start everything up and running I clone my personal Webpack boilerplate - This is still in Webpack 3, and does need some updating but gets the job done for now. So given the name of the repo you may have guessed that yes I am using Webpack as my bundler I use Webpack because it is so powerful, and even though it has a steep learning curve once you get it, its amazing.
The next thing I do is make sure my machine has Node.js configured and the right version installed then run Yarn. I decided to use Yarn because when I was building out this project npm had some shortcomings such as no .lock
file. I could probably move from Yarn to npm but I don't really see any point really.
I use Babel to transpile all of my #ES6 to #ES5 so the browser can read it, I love Babel and to be honest haven't looked up any other transpilers because Babel is amazing.
Finally when developing I have Prettier setup to make sure all my code is clean and uniform across all my JS files, and ESLint to make sure I catch any errors or code that could be optimized.
I'm really happy with this stack for my local env setup, and I'll probably stick with it for a while.
related Modernizr posts
related Modernizr posts
- Better than Underscore2
- Simple1
- Better that Underscore0
- It reduce the performance1