Edward Jackson

Edward Jackson


Build a Search Engine with Node.js and Elasticsearch

Originally published by Fernando Doglio at https://blog.logrocket.com

Many people tend to add a lot of mysticism around Google’s search algorithm (also known as Page Rank) because it somehow always manages to show us the result we’re looking for in the first few pages (even in those cases where there are hundreds of result pages).

How does it work? Why is it so accurate? There is no real answer to those questions unless of course, you’re part of the team inside Google working on maintaining it.

Without having to break into Google’s servers and steal their algorithm, we can work something out that’ll give us a very powerful search feature which you can easily integrate into your site/web app with very little effort and achieve a great user experience at the same time.

I’m essentially referring to what is normally known as a “full text search”. If you come from the traditional web development world, you’re probably used to having a SQL database, such as MySQL or PostgreSQL, which by default allow you to perform wildcard-based searches in your string fields, such as:

SELECT * FROM Cities WHERE name like 'new%';

Using the above query you would usually get matching results such as:

  • New York
  • New Delhi
  • New Orleans

You get the pattern, and if you had more complex objects inside your database, such as blog posts with a title and a body, you might also want to do a more “interesting” search on them, such as:

SELECT * FROM BLOG_POSTS WHERE title like '%2019%' OR body like '%2019%';

Now the above query would also yield some results, but what is the best order for these results? Does it make sense that a blog post that matched because the phone number 444220192 was inside its body, would be returned before one that has the title “The best soccer team of 2019”? The latter match is definitely more relevant, but a simple wildcard match would not be capable of doing that.

And because of that, adding a full-text search on your site might be a great match (especially if you want your users to search through unstructured content, such as FAQs, or downloadable documents to name a few examples).

Going full text

These are the use cases that leave basic wildcard searches behind. Granted, the most common SQL databases such as MySQL and PostgreSQL have included some form of basic full text capabilities, but if you want to take full advantage of this technique, you need a dedicated search engine, such as Elastic.

The way these engines work is by creating what is known as an “Inverted Index”. In the context of our example, where we’re trying to index text documents, they take each word from every document and record both the reference to the document they appear on and the position inside it. So instead of having to search for your substring inside each document (like you would with the above SQL examples), you only need to search for the substring inside the list of words, and those matching words will already know where they appear using the index.

The above diagram shows in a very simplified way, how an inverted index is built:

  1. Every word is listed on the index
  2. A reference to the source document is stored on every word (multiple references to different documents are allowed)
  3. Inside each document, we also record the position of the word (column #3)

With this information, we can simply search the index and match any coincidences between your query and the words in the index (we can even search using substrings and still return valid results).

This is still not getting us what we need since we don’t have any information about relevance. What’s more important a match on the title or the body? A full match or a partial match? These are rules our engine would need to know when searching and thankfully, the engine we’re going with today (Elastic) takes care of that and more.

So let’s take this basic inverted index and see how we can use Elastic to leverage this technique, shall we?

Going Elastic

Installing and running a local version of Elastic is really very straightforward, especially if you follow the official instructions.

Once you have it up and running, you’ll be able to interact with it using its RESTful API and any HTTP client you have on hand (I’ll be using curl, which should be installed in most common OS by default).

Once this is set, the real work can begin and don’t worry, I’ll walk you through all the following steps down the article:

  1. You’ll want to create an index
  2. After that, you’ll create a mapping for the documents inside the index
  3. Once everything is set, you’ll be able to index the documents
  4. Finally, searching will be possible

And to make things easier to understand, let’s assume we’re building a library’s API, one that’ll let you search through the content of different digital books.

For the purposes of this article, we’ll keep the metadata at a minimum, but you can add as much as you need for your particular use case. The books will be downloaded from the Gutenberg Project and will be manually indexed at first.

How to create your first index

Every indexed document in Elastic needs to be inserted, by definition, inside an index, that way you can easily search inside the scope you need if you start indexing different and unrelated objects.

If it makes it easier, you can think of an index as a container, and once you decide to search for something, you need to pick one container.

In order to create a new index, you can simply run this:

$ curl -X PUT localhost:9200/books

With that line, you’re sending your request to your localhost (assuming, of course, you’re doing a local test) and using port 9200 which is the default port for Elastic.

The path “books” is the actual index being created. A successful execution of the command would return something like:

  "acknowledged" : true,
  "shards_acknowledged" : true,
  "index" : "books"

For the time being, keep that path in mind, and let’s move on to the next step, creating a map.

How to create a map for your documents

This step is actually optional, you can define these parameters during execution of the query, but I’ve always found it easier to maintain an external mapping rather than one that is tied to your code’s business logic.

Here is where you can set up things such as:

  • What type of match can be done for the title of our books and the body (Is it a full match? do we use full text or basic matching? etc)
  • The weight of each match. Or in other words, how relevant is a match in the title versus a match in the body?

In order to create a mapping for a particular index, you’ll have to use the mappings endpoint and send the JSON describing the new mapping. Here is an example following the idea from above of indexing digital books:

  "properties": {
    "title": {
      "type": "text",
      "analyzer": "standard",
      "boost": 2
    "body": {
      "type": "text",
      "analyzer": "english"

This mapping defines two fields, the title, which needs to be analyzed with the standard analyzer and the body, which, considering these will all be English books, will use the language analyzer for English. I’m also adding a boost for matches on the title, which makes any of them twice as relevant as matches on the body of the book.

And in order to set this up on our index, all we need to do is use the following request:

$ curl -X PUT "localhost:9200/books?pretty" -H 'Content-Type: application/json' -d'
  "properties": {
    "title": {
      "type": "text",
      "analyzer": "standard",
      "boost": 2
    "body": {
      "type": "text",
      "analyzer": "english"

A successful execution would yield a result like this:

  "acknowledged" : true

Now with our index and mappings ready, all we have to do is start indexing and then perform a search.

How to index the content into Elastic

Even though technically, we can do this without coding, I’m going to create a quick script in Node.js to accelerate the process of sending the books into Elastic.

The script will be simple, it’ll read the content of the files from a particular directory, grab the first line and take it as the title, and then everything else will be indexed as part of the body.

Here’s that simple code:

const fs = require("fs")
const request = require("request-promise-native")
const util = require("util")

let files = [“60052-0.txt”, “60062-0.txt”, “60063-0.txt”, “pg60060.txt”]
const readFile = util.promisify(fs.readFile)

async function indexBook(fid, title, body) {
let url = “http://localhost:9200/books/_doc/” + fid
let payload = {
url: url,
body: {
title: title,
body: body.join(“\n”)
json: true
return request.put(payload)
( _ => {
files.forEach( async f => {
let book = await readFile(“./books/” + f);
[title, …body] = book.toString().split(“\n”);
try {
let result = await indexBook(f, title, body);
console.log("Indexing result: ", result);
} catch (err) {
console.log("ERROR: ", err)

All I’m doing is going through the list of books I have on my array, and sending their content to Elastic. The method used to index is PUT, and the path is your-host:your-port/index-name/_doc/a-doc-ID.

  • I’m using the default host and port (localhost and 9200)
  • My index is the one I created before: books
  • And the index I’m using is the file name, which I know is unique for each book

This essentially leaves us with a single thing to do, query our data.

How to query the index in Elastic

In order to query the index, we can use Elastic’s REST API the same way we’ve been using it so far, or we can move on to using Elastic’s official Node.js library.

In order to show something different, I’ll show you how to perform a search query using Elastic’s NPM module, feel free to check out their documentation if you want to start using it.

A quick example that should be enough to put into practice everything I’ve been discussing so far, would perform a full text search on the indexed documents and return a sorted list of results, based on relevancy (which is the default criteria Elastic uses).

The following code does exactly that, let me show you:

var elasticsearch = require(‘elasticsearch’);
var client = new elasticsearch.Client({
host: ‘localhost:9200/books’

let q = process.argv[2];

( async query => {
try {
const response = await client.search({
q: query
console.log(“Results found:”, response.hits.hits.length)
response.hits.hits.forEach( h => {
let {_source, …params } = h;
console.log("Result found in file: ", params._id, " with score: ", params._score)
} catch (error) {

The above code takes the first word you use as a CLI argument when executing the script and uses it as part of the query.

If you’re following along, you should be able to download and index some of the books from the Guterberng project and edit two of them. In one of them add the word “testing” as part of the first line, and in another one, add the same word, but in the middle of the text. That way you can see how relevancy works based on the mapping we setup.

In my case, these are the results I get:

Results found: 2
Result found in file: 60052-0.txt with score: 2.365865
Result found in file: pg60060.txt with score: 1.7539438

Thanks to the fact I used the filename as the document index, I can re-use that piece of information to show relevant results.

Essentially you can now download as many books as you like, and index them using the code from before. You have yourself a search engine, capable of quickly doing a search and returning the relevant filenames for you to open. The speed here is one of the benefits of using the inverted indexed I mentioned before since instead of having to comb through the entire body of each document every time, it’ll just search for the word you enter inside its internal index and return the list of references it made during indexing.

As a direct conclusion of this, you could safely say that indexing a document is far more expensive (computationally speaking) than searching. And since normally, most search engines spend most of their time searching instead of indexing, that is a completely fine trade-off.


That is it for my introduction to Elastic, I hope you found it as interesting as I do. Personally, this NoSQL database (as it is also known) is one of my favorites, thanks to the power you gain with very little code.

You can expand the above code with very little effort by categorizing the books and saving that information as part of the indexed metadata. After that, you can keep records of the types of books your users search for, and then adapt individual mappings with different boost values based on their preferences (i.e favoring sci-fi books for some users, while boosting history-based books for others). That would give you an even closer behavior to that of Google’s. Imagination is the limit!

Let me know down in the comments if you’ve used Elastic in the past and what kind of crazy search engine you have implemented!

Thanks for reading

If you liked this post, share it with all of your programming buddies!

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Further reading

The Complete Node.js Developer Course (3rd Edition)

Angular & NodeJS - The MEAN Stack Guide

NodeJS - The Complete Guide (incl. MVC, REST APIs, GraphQL)

Best 50 Nodejs interview questions from Beginners to Advanced in 2019

Node.js 12: The future of server-side JavaScript

An Introduction to Node.js Design Patterns

Basic Server Side Rendering with Vue.js and Express

Fullstack Vue App with MongoDB, Express.js and Node.js

How to create a full stack React/Express/MongoDB app using Docker

#node-js #javascript #web-development

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Buddha Community

Build a Search Engine with Node.js and Elasticsearch

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 "https://clojure.org")
                                (.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 "https://clojure.org")
       _ (-> (.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 [foo.bar :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: https://github.com/borkdude/nbb 
License: EPL-1.0

#node #javascript

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.

WebClues Infotech offers different levels of experienced and expert professionals for your app development needs. So hire a dedicated NodeJS developer from WebClues Infotech with your experience requirement and expertise.

So what are you waiting for? Get your app developed with strong performance parameters from WebClues Infotech

For inquiry click here: https://www.webcluesinfotech.com/hire-nodejs-developer/

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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!

Original Source

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Node JS Development Company| Node JS Web Developers-SISGAIN

Top organizations and start-ups hire Node.js developers from SISGAIN for their strategic software development projects in Illinois, USA. On the off chance that you are searching for a first rate innovation to assemble a constant Node.js web application development or a module, Node.js applications are the most appropriate alternative to pick. As Leading Node.js development company, we leverage our profound information on its segments and convey solutions that bring noteworthy business results. For more information email us at hello@sisgain.com

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sophia tondon

sophia tondon


Top 10 NodeJs app Development Companies- ValueCoders

Node.js is a prominent tech trend in the space of web and mobile application development. It has been proven very efficient and useful for a variety of application development. Thus, all business owners are eager to leverage this technology for creating their applications.

Are you striving to develop an application using Node.js? But can’t decide which company to hire for NodeJS app development? Well! Don’t stress over it, as the following list of NodeJS app development companies is going to help you find the best partner.

Let’s take a glance at top NodeJS application development companies to hire developers in 2021 for developing a mind-blowing application solution.

Before enlisting companies, I would like to say that every company has a foundation on which they thrive. Their end goals, qualities, and excellence define their competence. Thus, I prepared this list by considering a number of aspects. While making this list, I have considered the following aspects:

  • Review and rating
  • Enlisted by software peer & forums
  • Hourly price
  • Offered services
  • Year of experience (Average 8+ years)
  • Credibility & Excellence
  • Served clients and more

I believe this list will help you out in choosing the best NodeJS service provider company. So, now let’s explore the top NodeJS developer companies to choose from in 2021.

#1. JSGuru

JSGuru is a top-rated NodeJS app development company with an innovative team of dedicated NodeJS developers engaged in catering best-class UI/UX design, software products, and AWS professional services.

It is a team of one of the most talented developers to hire for all types of innovative solution development, including social media, dating, enterprise, and business-oriented solutions. The company has worked for years with a number of startups and launched a variety of products by collaborating with big-name corporations like T-systems.

If you want to hire NodeJS developers to secure an outstanding application, I would definitely suggest them. They serve in the area of eLearning, FinTech, eCommerce, Telecommunications, Mobile Device Management, and more.

  • Ratings: 4.9/5.0

  • Founded: 2006

  • Headquarters: Banja Luka, Bosnia, and Herzegovina

  • Price: Starting from $50/hour

Visit Website - https://www.valuecoders.com/blog/technology-and-apps/top-node-js-app-development-companies

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