Zak Dyer

Zak Dyer


Everything You Need to Understand Streams in Node.js

Node.js streams have a reputation for being hard to work with, and even harder to understand. Well I’ve got good news for you — that’s no longer the case.

Over the years, developers created lots of packages out there with the sole purpose of making working with streams easier. But in this article, I’m going to focus on the native Node.js stream API.

“Streams are Node’s best and most misunderstood idea.”

— Dominic Tarr

What exactly are streams?

Streams are collections of data — just like arrays or strings. The difference is that streams might not be available all at once, and they don’t have to fit in memory. This makes streams really powerful when working with large amounts of data, or data that’s coming from an external source one chunk at a time.

However, streams are not only about working with big data. They also give us the power of composability in our code. Just like we can compose powerful linux commands by piping other smaller Linux commands, we can do exactly the same in Node with streams.

const grep = ... // A stream for the grep output
const wc = ... // A stream for the wc input


Many of the built-in modules in Node implement the streaming interface:

The list above has some examples for native Node.js objects that are also readable and writable streams. Some of these objects are both readable and writable streams, like TCP sockets, zlib and crypto streams.

Notice that the objects are also closely related. While an HTTP response is a readable stream on the client, it’s a writable stream on the server. This is because in the HTTP case, we basically read from one object (http.IncomingMessage) and write to the other (http.ServerResponse).

Also note how the stdio streams (stdin, stdout, stderr) have the inverse stream types when it comes to child processes. This allows for a really easy way to pipe to and from these streams from the main process stdio streams.

A streams practical example

Theory is great, but often not 100% convincing. Let’s see an example demonstrating the difference streams can make in code when it comes to memory consumption.

Let’s create a big file first:

const fs = require('fs');
const file = fs.createWriteStream('./big.file');

for(let i=0; i<= 1e6; i++) {
  file.write('Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.\n');


Look what I used to create that big file. A writable stream!

The fs module can be used to read from and write to files using a stream interface. In the example above, we’re writing to that big.file through a writable stream 1 million lines with a loop.

Running the script above generates a file that’s about ~400 MB.

Here’s a simple Node web server designed to exclusively serve the big.file:

const fs = require('fs');
const server = require('http').createServer();

server.on('request', (req, res) => {
  fs.readFile('./big.file', (err, data) => {
    if (err) throw err;



When the server gets a request, it’ll serve the big file using the asynchronous method, fs.readFile. But hey, it’s not like we’re blocking the event loop or anything. Every thing is great, right? Right?

Well, let’s see what happens when we run the server, connect to it, and monitor the memory while doing so.

When I ran the server, it started out with a normal amount of memory, 8.7 MB:

Then I connected to the server. Note what happened to the memory consumed:

Wow — the memory consumption jumped to 434.8 MB.

We basically put the whole big.file content in memory before we wrote it out to the response object. This is very inefficient.

The HTTP response object (res in the code above) is also a writable stream. This means if we have a readable stream that represents the content of big.file, we can just pipe those two on each other and achieve mostly the same result without consuming ~400 MB of memory.

Node’s fs module can give us a readable stream for any file using the createReadStream method. We can pipe that to the response object:

const fs = require('fs');
const server = require('http').createServer();

server.on('request', (req, res) => {
  const src = fs.createReadStream('./big.file');


Now when you connect to this server, a magical thing happens (look at the memory consumption):

What’s happening?

When a client asks for that big file, we stream it one chunk at a time, which means we don’t buffer it in memory at all. The memory usage grew by about 25 MB and that’s it.

You can push this example to its limits. Regenerate the big.file with five million lines instead of just one million, which would take the file to well over 2 GB, and that’s actually bigger than the default buffer limit in Node.

If you try to serve that file using fs.readFile, you simply can’t, by default (you can change the limits). But with fs.createReadStream, there is no problem at all streaming 2 GB of data to the requester, and best of all, the process memory usage will roughly be the same.

Streams 101

There are four fundamental stream types in Node.js: Readable, Writable, Duplex, and Transform streams.

  • A readable stream is an abstraction for a source from which data can be consumed. An example of that is the fs.createReadStream method.
  • A writable stream is an abstraction for a destination to which data can be written. An example of that is the fs.createWriteStream method.
  • A duplex streams is both Readable and Writable. An example of that is a TCP socket.
  • A transform stream is basically a duplex stream that can be used to modify or transform the data as it is written and read. An example of that is the zlib.createGzip stream to compress the data using gzip. You can think of a transform stream as a function where the input is the writable stream part and the output is readable stream part. You might also hear transform streams referred to as “through streams.”

All streams are instances of EventEmitter. They emit events that can be used to read and write data. However, we can consume streams data in a simpler way using the pipe method.

The pipe method

Here’s the magic line that you need to remember:


In this simple line, we’re piping the output of a readable stream — the source of data, as the input of a writable stream — the destination. The source has to be a readable stream and the destination has to be a writable one. Of course, they can both be duplex/transform streams as well. In fact, if we’re piping into a duplex stream, we can chain pipe calls just like we do in Linux:


The pipe method returns the destination stream, which enabled us to do the chaining above. For streams a (readable), b and c (duplex), and d (writable), we can:


# Which is equivalent to:

# Which, in Linux, is equivalent to:
$ a | b | c | d

The pipe method is the easiest way to consume streams. It’s generally recommended to either use the pipe method or consume streams with events, but avoid mixing these two. Usually when you’re using the pipe method you don’t need to use events, but if you need to consume the streams in more custom ways, events would be the way to go.

Stream events

Beside reading from a readable stream source and writing to a writable destination, the pipe method automatically manages a few things along the way. For example, it handles errors, end-of-files, and the cases when one stream is slower or faster than the other.

However, streams can also be consumed with events directly. Here’s the simplified event-equivalent code of what the pipe method mainly does to read and write data:

# readable.pipe(writable)

readable.on('data', (chunk) => {

readable.on('end', () => {

Here’s a list of the important events and functions that can be used with readable and writable streams:

The events and functions are somehow related because they are usually used together.

The most important events on a readable stream are:

  • The data event, which is emitted whenever the stream passes a chunk of data to the consumer
  • The end event, which is emitted when there is no more data to be consumed from the stream.

The most important events on a writable stream are:

  • The drain event, which is a signal that the writable stream can receive more data.
  • The finish event, which is emitted when all data has been flushed to the underlying system.

Events and functions can be combined to make for a custom and optimized use of streams. To consume a readable stream, we can use the pipe/unpipe methods, or the read/unshift/resume methods. To consume a writable stream, we can make it the destination of pipe/unpipe, or just write to it with the write method and call the end method when we’re done.

Paused and Flowing Modes of Readable Streams

Readable streams have two main modes that affect the way we can consume them:

  • They can be either in the paused mode
  • Or in the flowing mode

Those modes are sometimes referred to as pull and push modes.

All readable streams start in the paused mode by default but they can be easily switched to flowing and back to paused when needed. Sometimes, the switching happens automatically.

When a readable stream is in the paused mode, we can use the read() method to read from the stream on demand, however, for a readable stream in the flowing mode, the data is continuously flowing and we have to listen to events to consume it.

In the flowing mode, data can actually be lost if no consumers are available to handle it. This is why, when we have a readable stream in flowing mode, we need a data event handler. In fact, just adding a data event handler switches a paused stream into flowing mode and removing the data event handler switches the stream back to paused mode. Some of this is done for backward compatibility with the older Node streams interface.

To manually switch between these two stream modes, you can use the resume() and pause() methods.

When consuming readable streams using the pipe method, we don’t have to worry about these modes as pipe manages them automatically.

Implementing Streams

When we talk about streams in Node.js, there are two main different tasks:

  • The task of implementing the streams.
  • The task of consuming them.

So far we’ve been talking about only consuming streams. Let’s implement some!

Stream implementers are usually the ones who require the stream module.

Implementing a Writable Stream

To implement a writable stream, we need to to use the Writable constructor from the stream module.

const { Writable } = require('stream');

We can implement a writable stream in many ways. We can, for example, extend the Writable constructor if we want

class myWritableStream extends Writable {

However, I prefer the simpler constructor approach. We just create an object from the Writable constructor and pass it a number of options. The only required option is a write function which exposes the chunk of data to be written.

const { Writable } = require('stream');

const outStream = new Writable({
  write(chunk, encoding, callback) {


This write method takes three arguments.

  • The chunk is usually a buffer unless we configure the stream differently.
  • The encoding argument is needed in that case, but usually we can ignore it.
  • The callback is a function that we need to call after we’re done processing the data chunk. It’s what signals whether the write was successful or not. To signal a failure, call the callback with an error object.

In outStream, we simply console.log the chunk as a string and call the callback after that without an error to indicate success. This is a very simple and probably not so useful echo stream. It will echo back anything it receives.

To consume this stream, we can simply use it with process.stdin, which is a readable stream, so we can just pipe process.stdin into our outStream.

When we run the code above, anything we type into process.stdin will be echoed back using the outStream console.log line.

This is not a very useful stream to implement because it’s actually already implemented and built-in. This is very much equivalent to process.stdout. We can just pipe stdin into stdout and we’ll get the exact same echo feature with this single line:


Implement a Readable Stream

To implement a readable stream, we require the Readable interface, and construct an object from it, and implement a read() method in the stream’s configuration parameter:

const { Readable } = require('stream');

const inStream = new Readable({
  read() {}

There is a simple way to implement readable streams. We can just directly push the data that we want the consumers to consume.

const { Readable } = require('stream'); 

const inStream = new Readable({
  read() {}


inStream.push(null); // No more data


When we push a null object, that means we want to signal that the stream does not have any more data.

To consume this simple readable stream, we can simply pipe it into the writable stream process.stdout.

When we run the code above, we’ll be reading all the data from inStream and echoing it to the standard out. Very simple, but also not very efficient.

We’re basically pushing all the data in the stream before piping it to process.stdout. The much better way is to push data on demand, when a consumer asks for it. We can do that by implementing the read() method in the configuration object:

const inStream = new Readable({
  read(size) {
    // there is a demand on the data... Someone wants to read it.

When the read method is called on a readable stream, the implementation can push partial data to the queue. For example, we can push one letter at a time, starting with character code 65 (which represents A), and incrementing that on every push:

const inStream = new Readable({
  read(size) {
    if (this.currentCharCode > 90) {

inStream.currentCharCode = 65;


While the consumer is reading a readable stream, the read method will continue to fire, and we’ll push more letters. We need to stop this cycle somewhere, and that’s why an if statement to push null when the currentCharCode is greater than 90 (which represents Z).

This code is equivalent to the simpler one we started with but now we’re pushing data on demand when the consumer asks for it. You should always do that.

Implementing Duplex/Transform Streams

With Duplex streams, we can implement both readable and writable streams with the same object. It’s as if we inherit from both interfaces.

Here’s an example duplex stream that combines the two writable and readable examples implemented above:

const { Duplex } = require('stream');

const inoutStream = new Duplex({
  write(chunk, encoding, callback) {

  read(size) {
    if (this.currentCharCode > 90) {

inoutStream.currentCharCode = 65;


By combining the methods, we can use this duplex stream to read the letters from A to Z and we can also use it for its echo feature. We pipe the readable stdin stream into this duplex stream to use the echo feature and we pipe the duplex stream itself into the writable stdout stream to see the letters A through Z.

It’s important to understand that the readable and writable sides of a duplex stream operate completely independently from one another. This is merely a grouping of two features into an object.

A transform stream is the more interesting duplex stream because its output is computed from its input.

For a transform stream, we don’t have to implement the read or write methods, we only need to implement a transform method, which combines both of them. It has the signature of the write method and we can use it to push data as well.

Here’s a simple transform stream which echoes back anything you type into it after transforming it to upper case format:

const { Transform } = require('stream');

const upperCaseTr = new Transform({
  transform(chunk, encoding, callback) {


In this transform stream, which we’re consuming exactly like the previous duplex stream example, we only implemented a transform() method. In that method, we convert the chunk into its upper case version and then push that version as the readable part.

Streams Object Mode

By default, streams expect Buffer/String values. There is an objectMode flag that we can set to have the stream accept any JavaScript object.

Here’s a simple example to demonstrate that. The following combination of transform streams makes for a feature to map a string of comma-separated values into a JavaScript object. So “a,b,c,d” becomes {a: b, c: d}.

const { Transform } = require('stream');

const commaSplitter = new Transform({
  readableObjectMode: true,

  transform(chunk, encoding, callback) {

const arrayToObject = new Transform({
  readableObjectMode: true,
  writableObjectMode: true,

  transform(chunk, encoding, callback) {
    const obj = {};
    for(let i=0; i < chunk.length; i+=2) {
      obj[chunk[i]] = chunk[i+1];

const objectToString = new Transform({
  writableObjectMode: true,

  transform(chunk, encoding, callback) {
    this.push(JSON.stringify(chunk) + '\n');


We pass the input string (for example, “a,b,c,d”) through commaSplitter which pushes an array as its readable data ([“a”, “b”, “c”, “d”]). Adding the readableObjectMode flag on that stream is necessary because we’re pushing an object there, not a string.

We then take the array and pipe it into the arrayToObject stream. We need a writableObjectMode flag to make that stream accept an object. It’ll also push an object (the input array mapped into an object) and that’s why we also needed the readableObjectMode flag there as well. The last objectToString stream accepts an object but pushes out a string, and that’s why we only needed a writableObjectMode flag there. The readable part is a normal string (the stringified object).

Node’s built-in transform streams

Node has a few very useful built-in transform streams. Namely, the zlib and crypto streams.

Here’s an example that uses the zlib.createGzip() stream combined with the fs readable/writable streams to create a file-compression script:

const fs = require('fs');
const zlib = require('zlib');
const file = process.argv[2];

  .pipe(fs.createWriteStream(file + '.gz'));

You can use this script to gzip any file you pass as the argument. We’re piping a readable stream for that file into the zlib built-in transform stream and then into a writable stream for the new gzipped file. Simple.

The cool thing about using pipes is that we can actually combine them with events if we need to. Say, for example, I want the user to see a progress indicator while the script is working and a “Done” message when the script is done. Since the pipe method returns the destination stream, we can chain the registration of events handlers as well:

const fs = require('fs');
const zlib = require('zlib');
const file = process.argv[2];

  .on('data', () => process.stdout.write('.'))
  .pipe(fs.createWriteStream(file + '.zz'))
  .on('finish', () => console.log('Done'));

So with the pipe method, we get to easily consume streams, but we can still further customize our interaction with those streams using events where needed.

What’s great about the pipe method though is that we can use it to compose our program piece by piece, in a much readable way. For example, instead of listening to the data event above, we can simply create a transform stream to report progress, and replace the .on() call with another .pipe() call:

const fs = require('fs');
const zlib = require('zlib');
const file = process.argv[2];

const { Transform } = require('stream');

const reportProgress = new Transform({
  transform(chunk, encoding, callback) {
    callback(null, chunk);

  .pipe(fs.createWriteStream(file + '.zz'))
  .on('finish', () => console.log('Done'));

This reportProgress stream is a simple pass-through stream, but it reports the progress to standard out as well. Note how I used the second argument in the callback() function to push the data inside the transform() method. This is equivalent to pushing the data first.

The applications of combining streams are endless. For example, if we need to encrypt the file before or after we gzip it, all we need to do is pipe another transform stream in that exact order that we needed. We can use Node’s crypto module for that:

const crypto = require('crypto');
// ...

  .pipe(crypto.createCipher('aes192', 'a_secret'))
  .pipe(fs.createWriteStream(file + '.zz'))
  .on('finish', () => console.log('Done'));

The script above compresses and then encrypts the passed file and only those who have the secret can use the outputted file. We can’t unzip this file with the normal unzip utilities because it’s encrypted.

To actually be able to unzip anything zipped with the script above, we need to use the opposite streams for crypto and zlib in a reverse order, which is simple:

  .pipe(crypto.createDecipher('aes192', 'a_secret'))
  .pipe(fs.createWriteStream(file.slice(0, -3)))
  .on('finish', () => console.log('Done'));

Assuming the passed file is the compressed version, the code above will create a read stream from that, pipe it into the crypto createDecipher() stream (using the same secret), pipe the output of that into the zlib createGunzip() stream, and then write things out back to a file without the extension part.

Thanks for reading!

#nodejs #node #javascript #webdev #databases

What is GEEK

Buddha Community

Everything You Need to Understand Streams in Node.js

NBB: Ad-hoc CLJS Scripting on Node.js


Not babashka. Node.js babashka!?

Ad-hoc CLJS scripting on Node.js.


Experimental. Please report issues here.

Goals and features

Nbb's main goal is to make it easy to get started with ad hoc CLJS scripting on Node.js.

Additional goals and features are:

  • Fast startup without relying on a custom version of Node.js.
  • Small artifact (current size is around 1.2MB).
  • First class macros.
  • Support building small TUI apps using Reagent.
  • Complement babashka with libraries from the Node.js ecosystem.


Nbb requires Node.js v12 or newer.

How does this tool work?

CLJS code is evaluated through SCI, the same interpreter that powers babashka. Because SCI works with advanced compilation, the bundle size, especially when combined with other dependencies, is smaller than what you get with self-hosted CLJS. That makes startup faster. The trade-off is that execution is less performant and that only a subset of CLJS is available (e.g. no deftype, yet).


Install nbb from NPM:

$ npm install nbb -g

Omit -g for a local install.

Try out an expression:

$ nbb -e '(+ 1 2 3)'

And then install some other NPM libraries to use in the script. E.g.:

$ npm install csv-parse shelljs zx

Create a script which uses the NPM libraries:

(ns script
  (:require ["csv-parse/lib/sync$default" :as csv-parse]
            ["fs" :as fs]
            ["path" :as path]
            ["shelljs$default" :as sh]
            ["term-size$default" :as term-size]
            ["zx$default" :as zx]
            ["zx$fs" :as zxfs]
            [nbb.core :refer [*file*]]))

(prn (path/resolve "."))

(prn (term-size))

(println (count (str (fs/readFileSync *file*))))

(prn (sh/ls "."))

(prn (csv-parse "foo,bar"))

(prn (zxfs/existsSync *file*))

(zx/$ #js ["ls"])

Call the script:

$ nbb script.cljs
#js {:columns 216, :rows 47}
#js ["node_modules" "package-lock.json" "package.json" "script.cljs"]
#js [#js ["foo" "bar"]]
$ ls


Nbb has first class support for macros: you can define them right inside your .cljs file, like you are used to from JVM Clojure. Consider the plet macro to make working with promises more palatable:

(defmacro plet
  [bindings & body]
  (let [binding-pairs (reverse (partition 2 bindings))
        body (cons 'do body)]
    (reduce (fn [body [sym expr]]
              (let [expr (list '.resolve 'js/Promise expr)]
                (list '.then expr (list 'clojure.core/fn (vector sym)

Using this macro we can look async code more like sync code. Consider this puppeteer example:

(-> (.launch puppeteer)
      (.then (fn [browser]
               (-> (.newPage browser)
                   (.then (fn [page]
                            (-> (.goto page "")
                                (.then #(.screenshot page #js{:path "screenshot.png"}))
                                (.catch #(js/console.log %))
                                (.then #(.close browser)))))))))

Using plet this becomes:

(plet [browser (.launch puppeteer)
       page (.newPage browser)
       _ (.goto page "")
       _ (-> (.screenshot page #js{:path "screenshot.png"})
             (.catch #(js/console.log %)))]
      (.close browser))

See the puppeteer example for the full code.

Since v0.0.36, nbb includes promesa which is a library to deal with promises. The above plet macro is similar to promesa.core/let.

Startup time

$ time nbb -e '(+ 1 2 3)'
nbb -e '(+ 1 2 3)'   0.17s  user 0.02s system 109% cpu 0.168 total

The baseline startup time for a script is about 170ms seconds on my laptop. When invoked via npx this adds another 300ms or so, so for faster startup, either use a globally installed nbb or use $(npm bin)/nbb script.cljs to bypass npx.


NPM dependencies

Nbb does not depend on any NPM dependencies. All NPM libraries loaded by a script are resolved relative to that script. When using the Reagent module, React is resolved in the same way as any other NPM library.


To load .cljs files from local paths or dependencies, you can use the --classpath argument. The current dir is added to the classpath automatically. So if there is a file foo/bar.cljs relative to your current dir, then you can load it via (:require [ :as fb]). Note that nbb uses the same naming conventions for namespaces and directories as other Clojure tools: foo-bar in the namespace name becomes foo_bar in the directory name.

To load dependencies from the Clojure ecosystem, you can use the Clojure CLI or babashka to download them and produce a classpath:

$ classpath="$(clojure -A:nbb -Spath -Sdeps '{:aliases {:nbb {:replace-deps {com.github.seancorfield/honeysql {:git/tag "v2.0.0-rc5" :git/sha "01c3a55"}}}}}')"

and then feed it to the --classpath argument:

$ nbb --classpath "$classpath" -e "(require '[honey.sql :as sql]) (sql/format {:select :foo :from :bar :where [:= :baz 2]})"
["SELECT foo FROM bar WHERE baz = ?" 2]

Currently nbb only reads from directories, not jar files, so you are encouraged to use git libs. Support for .jar files will be added later.

Current file

The name of the file that is currently being executed is available via nbb.core/*file* or on the metadata of vars:

(ns foo
  (:require [nbb.core :refer [*file*]]))

(prn *file*) ;; "/private/tmp/foo.cljs"

(defn f [])
(prn (:file (meta #'f))) ;; "/private/tmp/foo.cljs"


Nbb includes reagent.core which will be lazily loaded when required. You can use this together with ink to create a TUI application:

$ npm install ink


(ns ink-demo
  (:require ["ink" :refer [render Text]]
            [reagent.core :as r]))

(defonce state (r/atom 0))

(doseq [n (range 1 11)]
  (js/setTimeout #(swap! state inc) (* n 500)))

(defn hello []
  [:> Text {:color "green"} "Hello, world! " @state])

(render (r/as-element [hello]))


Working with callbacks and promises can become tedious. Since nbb v0.0.36 the promesa.core namespace is included with the let and do! macros. An example:

(ns prom
  (:require [promesa.core :as p]))

(defn sleep [ms]
   (fn [resolve _]
     (js/setTimeout resolve ms))))

(defn do-stuff
   (println "Doing stuff which takes a while")
   (sleep 1000)

(p/let [a (do-stuff)
        b (inc a)
        c (do-stuff)
        d (+ b c)]
  (prn d))
$ nbb prom.cljs
Doing stuff which takes a while
Doing stuff which takes a while

Also see API docs.


Since nbb v0.0.75 applied-science/js-interop is available:

(ns example
  (:require [applied-science.js-interop :as j]))

(def o (j/lit {:a 1 :b 2 :c {:d 1}}))

(prn (j/select-keys o [:a :b])) ;; #js {:a 1, :b 2}
(prn (j/get-in o [:c :d])) ;; 1

Most of this library is supported in nbb, except the following:

  • destructuring using :syms
  • property access using .-x notation. In nbb, you must use keywords.

See the example of what is currently supported.


See the examples directory for small examples.

Also check out these projects built with nbb:


See API documentation.

Migrating to shadow-cljs

See this gist on how to convert an nbb script or project to shadow-cljs.



  • babashka >= 0.4.0
  • Clojure CLI >=
  • Node.js 16.5.0 (lower version may work, but this is the one I used to build)

To build:

  • Clone and cd into this repo
  • bb release

Run bb tasks for more project-related tasks.

Download Details:
Author: borkdude
Download Link: Download The Source Code
Official Website: 
License: EPL-1.0

#node #javascript

Marlon  Boyle

Marlon Boyle


Hands on with Node.Js Streams | Examples & Approach

Never heard of Node.js? Node.js is an accessible asynchronous environment based on Javascript which contains several core modules helpful for performing various tasks. Node.js is famous worldwide due to its efficiency and being open-source, it brings a lot to the table. Node.js allows the developers to handle multiple requests on a single thread and thereby allowing them more breathing space.

Node.js handles data using two approaches – Buffered and Streamed. In the buffered approach, you have to write the entire data before the receiver may read it. Such an approach doesn’t support its asynchronous paradigm. When it comes to the Streamed approach, the information starts the interpreting process as soon as you enter it.

Before you read further, we would like to inform you that this article is about streams. Streams are an essential part of the Node.js environment. What it stream, and what do they do? What are the different types of streams? We have tried to cover several important questions that may help you in understanding Node.js Streams. Let’s get started.

#nodejs #streams in node.js #using streams in node js #node.js streams #node.js tutorial #data streams

Hire Dedicated Node.js Developers - Hire Node.js Developers

If you look at the backend technology used by today’s most popular apps there is one thing you would find common among them and that is the use of NodeJS Framework. Yes, the NodeJS framework is that effective and successful.

If you wish to have a strong backend for efficient app performance then have NodeJS at the backend.

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Aria Barnes

Aria Barnes


Why use Node.js for Web Development? Benefits and Examples of Apps

Front-end web development has been overwhelmed by JavaScript highlights for quite a long time. Google, Facebook, Wikipedia, and most of all online pages use JS for customer side activities. As of late, it additionally made a shift to cross-platform mobile development as a main technology in React Native, Nativescript, Apache Cordova, and other crossover devices. 

Throughout the most recent couple of years, Node.js moved to backend development as well. Designers need to utilize a similar tech stack for the whole web project without learning another language for server-side development. Node.js is a device that adjusts JS usefulness and syntax to the backend. 

What is Node.js? 

Node.js isn’t a language, or library, or system. It’s a runtime situation: commonly JavaScript needs a program to work, however Node.js makes appropriate settings for JS to run outside of the program. It’s based on a JavaScript V8 motor that can run in Chrome, different programs, or independently. 

The extent of V8 is to change JS program situated code into machine code — so JS turns into a broadly useful language and can be perceived by servers. This is one of the advantages of utilizing Node.js in web application development: it expands the usefulness of JavaScript, permitting designers to coordinate the language with APIs, different languages, and outside libraries.

What Are the Advantages of Node.js Web Application Development? 

Of late, organizations have been effectively changing from their backend tech stacks to Node.js. LinkedIn picked Node.js over Ruby on Rails since it took care of expanding responsibility better and decreased the quantity of servers by multiple times. PayPal and Netflix did something comparative, just they had a goal to change their design to microservices. We should investigate the motivations to pick Node.JS for web application development and when we are planning to hire node js developers. 

Amazing Tech Stack for Web Development 

The principal thing that makes Node.js a go-to environment for web development is its JavaScript legacy. It’s the most well known language right now with a great many free devices and a functioning local area. Node.js, because of its association with JS, immediately rose in ubiquity — presently it has in excess of 368 million downloads and a great many free tools in the bundle module. 

Alongside prevalence, Node.js additionally acquired the fundamental JS benefits: 

  • quick execution and information preparing; 
  • exceptionally reusable code; 
  • the code is not difficult to learn, compose, read, and keep up; 
  • tremendous asset library, a huge number of free aides, and a functioning local area. 

In addition, it’s a piece of a well known MEAN tech stack (the blend of MongoDB, Express.js, Angular, and Node.js — four tools that handle all vital parts of web application development). 

Designers Can Utilize JavaScript for the Whole Undertaking 

This is perhaps the most clear advantage of Node.js web application development. JavaScript is an unquestionable requirement for web development. Regardless of whether you construct a multi-page or single-page application, you need to know JS well. On the off chance that you are now OK with JavaScript, learning Node.js won’t be an issue. Grammar, fundamental usefulness, primary standards — every one of these things are comparable. 

In the event that you have JS designers in your group, it will be simpler for them to learn JS-based Node than a totally new dialect. What’s more, the front-end and back-end codebase will be basically the same, simple to peruse, and keep up — in light of the fact that they are both JS-based. 

A Quick Environment for Microservice Development 

There’s another motivation behind why Node.js got famous so rapidly. The environment suits well the idea of microservice development (spilling stone monument usefulness into handfuls or many more modest administrations). 

Microservices need to speak with one another rapidly — and Node.js is probably the quickest device in information handling. Among the fundamental Node.js benefits for programming development are its non-obstructing algorithms.

Node.js measures a few demands all at once without trusting that the first will be concluded. Many microservices can send messages to one another, and they will be gotten and addressed all the while. 

Versatile Web Application Development 

Node.js was worked in view of adaptability — its name really says it. The environment permits numerous hubs to run all the while and speak with one another. Here’s the reason Node.js adaptability is better than other web backend development arrangements. 

Node.js has a module that is liable for load adjusting for each running CPU center. This is one of numerous Node.js module benefits: you can run various hubs all at once, and the environment will naturally adjust the responsibility. 

Node.js permits even apportioning: you can part your application into various situations. You show various forms of the application to different clients, in light of their age, interests, area, language, and so on. This builds personalization and diminishes responsibility. Hub accomplishes this with kid measures — tasks that rapidly speak with one another and share a similar root. 

What’s more, Node’s non-hindering solicitation handling framework adds to fast, letting applications measure a great many solicitations. 

Control Stream Highlights

Numerous designers consider nonconcurrent to be one of the two impediments and benefits of Node.js web application development. In Node, at whatever point the capacity is executed, the code consequently sends a callback. As the quantity of capacities develops, so does the number of callbacks — and you end up in a circumstance known as the callback damnation. 

In any case, Node.js offers an exit plan. You can utilize systems that will plan capacities and sort through callbacks. Systems will associate comparable capacities consequently — so you can track down an essential component via search or in an envelope. At that point, there’s no compelling reason to look through callbacks.


Final Words

So, these are some of the top benefits of Nodejs in web application development. This is how Nodejs is contributing a lot to the field of web application development. 

I hope now you are totally aware of the whole process of how Nodejs is really important for your web project. If you are looking to hire a node js development company in India then I would suggest that you take a little consultancy too whenever you call. 

Good Luck!

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