Netflix vs. Hulu, Hubspot vs. Salesforce, Spotify vs. Pandora, Databrick vs. ByteDance, Canva vs. Miro, and Uber vs Lyft are the rivalries that interest most entrepreneurs and startup owners looking to create their solutions in the niche.

Why? Because knowledge is power. Once you know what’s under the hood of the most prominent tech giants of the 21st century, planning a tech stack for your own business is much easier. Learning about prominent companies’ choices shows what languages, tools, and frameworks have already proved to be effective in the field.

First, let’s explore what a tech stack is before diving deep into what’s happening behind the curtains of the applications that millions of people use every day.

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What is a tech stack?

A tech stack is the selection of technologies used to power every aspect of a product from the backend. It includes hosting and cloud storage. Put simply, a tech stack is essential for all the instruments and materials your development team will use to build an app from the ground up. 

Why do tech stacks matter?

Choosing a tech stack is a strategic decision. It has a lasting impact on the entire development lifecycle and even beyond. The same tasks can be solved by various technologies, and you need to find the ones that fit your individual needs, i.e. the ones that are effective and cost-efficient.


If you are unsure what to choose, you can tell us about your project at a free consultation. Our Delivery Managers will carefully consider your case and offer the most suitable and profitable solution for the launch and growth of your business.


Why do tech stacks of other companies matter?

Not every coding language, cloud storage, framework, or virtual machine is made equal. More on the matter, most are designed to address a very specific set of challenges. 

Let's take a look at Python, for example. It is an interpreted, high-level language that, according to its common description, is used for general-purpose programming. It's true to an extent: you can, in theory, code anything you want with it. You can use Python to develop a Data Science app, a Web scraping tool, AI, or IoT products. It would be much harder to develop a web page's front-end or a mobile app using Python.

If you try to use Python to develop things it's not designed for, you will be spending more time, doing excessive reworks, and investing heavily in third-party tools. The entire development process will become problematic for the team and the investors. 

Opening a wine bottle with a fork is possible, but why bother when there's a perfectly good corkscrew around? 

This is exactly why many businesses spy on the market's most successful products to see what fitting solutions those have found.

Without further ado, let's take a look at the tech stacks of the most prominent Tech companies.

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Video streaming servises 

The online streaming services market is fragmented. So vendors to attract more users are deploying growth strategies such as offering advanced products or expanding their businesses to new regions to compete in the market.

During the COVID-19 pandemic, platforms have registered a spike in their viewership worldwide. Because the pandemic has restricted people from staying indoors for a prolonged period. As a result of this situation, streaming services' viewership and engagement increased, resulting in service video demand.

The global video streaming market is expected to reach USD 330.51 billion by 2030, with a compound annual growth rate of 21.3% from 2022 to 2030. The market is expected to grow due to technological advancements such as blockchain technology and AI to improve the quality of videos.

Global Video Streaming Market

What is Netflix tech stack

Some might argue that Netflix owes its success to the vast availability of stunning content, but that is only partially true. After all, what's the point of having critically acclaimed shows in a place where no one can see them?

The Netflix app is based on multiple programming languages: Python, Node.JS, Java, Kotlin, and Swift. This is done to ensure all-round compatibility of the Netflix app across multiple platforms: browsers, smart TVs, smartphones, and gaming consoles. 

The comprehensive library part of the stack is designed to offer users the most polished experience they've grown to expect from a streaming service. Netflix owes its user-friendly interface to React and JS UI libraries. 

Given the app's heavy emphasis on cloud-based solutions, the team behind the streaming giant has opted to use Dynomite as the database cluster management service. It offers several exceptional advantages: for example, support for in-memory, pluggable, and persistent storage engines.


You can also get our free consultation if you need more expertise in developing and supporting streaming services like Netflix. We are always ready to provide our best software and mobile app development practices.


Application and data used to Netflix

Python Logo.

Python

Node JS

Node JS

React

React

Java

Java

MySQL

MySQL

PostgresSQL

PostgresSQL

Flask

Flask

Oracle

Oracle

Cassandra

Cassandra

Presto

Presto

Amazon EC2

Amazon EC2

Amazon S3

Amazon S3

Amazon RDS

Amazon RDS

Amazon DynamoDB

Amazon DynamoDB

 Amazon Elastic MapReduce

Amazon Elastic MapReduce

CloudBees

CloudBees

Apache Pig

Apache Pig

Win JS

Win JS

Atlas-DB

Atlas-DB by Netflix

DevOps technologies used to Netflix

Jenkins

Jenkins

GitHub

GitHub

Grandle

Grandle

Git

Git

Apache Mesos

Apache Mesos

Sumo Logic

Sumo Logic

Crittercism

Crittercism

Vector

Vector

Boundary

Boundary

Dynomite

Dynomite

AWS CloudTrail

AWS CloudTrail

Express Gateway

Express Gateway

LogicMonitor

LogicMonitor

Business tools and utilities used to Netflix

Confuence

Confuence

OneLogin

OneLogin

G Suite

G Suite

HubCommander

HubCommander by Netflix

Amazon SES

Amazon SES

Urban Airship

Urban Airship

Falcor

Falcor

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What is Hulu tech stack

In 2007, Hulu made its debut on the web using a monolithic application written in Rails and jQuery. This architecture benefited Hulu at the startup stage by simplifying development and deployment efforts, but as the company, product, and engineering teams grew, new architectural challenges emerged. 

Hulu Web applications are now built using Node.js. They chose to React as a UI library. The state management challenge is solved by React's own component state. In order to push the limits of web performance, server-side rendering is preferred. Next.js was chosen as the underlying framework.

To test React, they chose Jest and react-testing-library. Since the first commit, they have required 100% coverage of unit tests.

Application, data, and DevOps technologies used to Hulu

Python Logo.

Python

NGINX

NGINX

Redis

Redis

Ruby

Ruby

Rails

Ruby on Rails

Golang Logo.

Golang

Backbone js

Backbone JS

Handlebars

Handlebars JS

Cassandra

Cassandra

Underscore

Underscore JS

Amazon Aurora

Amazon Aurora

Git

Git

Salt

Salt

Business tools and utilities used to Hulu

Jira

Jira

Zendesk

Zendesk

Google Analytics

Google Analytics

Twilio

Twilio

Flurry

Flurry

UserTesting

UserTesting

CRM platforms

A customer relationship management system (CRM) is tool companies use to manage relationships and interactions with their customers and potential customers. The main goal of this platform is: Improve business relationships. 

The global customer relationship management market size was valued at USD 52.4 billion in 2021. From 2022 to 2030, the global customer relationship management market is expected to grow at a CAGR of 13.3%.

Customer Relationship Management Market

Growing demand for CRM solutions worldwide is driven by the need to automate customer engagement, improve digital operations, and enhance customer experience and services. The market is expected to be driven by emerging technologies, including cloud computing, AI, machine learning, and various service models, including SaaS, Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).

HubSpot tech stack

HubSpot is a cloud-based CRM platform. The HubSpot CMS was launched in April 2020.  This platform is designed to connect everything scaling companies need to deliver a best-in-class customer experience into one place.

In addition to being easy to use, HubSpot is also incredibly easy to create with. For example, landing pages, forms, and emails can be created using drag-and-drop. Additionally, you can bulk-create and schedule social media content. Businesses that don't have the time to create these kinds of content will greatly benefit from this.

HubSpot has grown revenues by 40%, compounded annually since 2014. Additionally, the business has a high retention rate and has gradually improved its profitability and free cash flow. From its all-time highs in November 2021, the stock price has been butchered by 67%. In this post, let's take a closer look at the company's business model, financials, and valuation. As of October 2022, HubSpot has a market cap of $14.24 Billion.

Application and data technologies used to HubSpot

JS

JavaScript

React

React

Java

Java

MySQL

MySQL

NGINX

NGINX

Cloudflare

Cloudflare

ES6

ES6

Amazon S3

Amazon S3

Sass

Sass

Kafka

Kafka

Swift

Swift

Spark

Spark

Hadoop

Hadoop

HBase

HBase

Vitess

Vitess

DevOps technologies used to HubSpot

Kubernetes

Kubernetes

IntelliJ IDEA

IntelliJ IDEA

GitHub

GitHub

Git

Git

Docker

Docker

Sublime Text

Sublime Text

Kibana

Kibana

Atom

Atom

Selenium

Selenium

Sentry

Sentry

PagerDuty

PagerDuty

OpenStack

OpenStack

Apache Mesos

Apache Mesos

Business tools and utilities used to HubSpot

Jira

Jira

Confuence

Confuence

Slack

Slack

inVision

inVision

Elasticsearch

Elasticsearch

Stripe

Stripe

GitHub Pages

GitHub Pages

Okta

Okta

FullContact

FullContact

Salesforce tech stack

A lot about the tech stack behind Salesforce itself is not public knowledge, but one can figure out a lot from the assortment of tools the company is known to use. 

As with all large-scale projects that support thousands of users in real time, the primary focus is scalability. Then comes usability on a multitude of platforms, including web browsers and native mobile applications. And, of course, data storage and security are pivotal, given the number of contacts and deals users store in their Salesforce accounts. 

Also, Salesforce features custom-built analytics tools and complex search and analysis algorithms.

Application, data, and DevOps technologies used to Salesforce

Jenkins

Jenkins

Cloudant

Cloudant

Akamai

Akamai

ClearDB

MySQL ClearDB

Bitbucket

Bitbucket

New Relic

New Relic

Datadog

Datadog

Puppet Labs

Puppet Labs

Cloud9 IDE

Cloud9 IDE

Sauce Labs

Sauce Labs

Business tools and utilities used to Salesforce

Salesforce Sales Cloud

Salesforce Sales Cloud

Jira

Jira

G Suite

G Suite

inVision

inVision

Balsamiq

Balsamiq

DocuSign

DocuSign

UXPin

UXPin

Google Analytics

Google Analytics

Twilio

Twilio

Optimizely

Optimizely

Heap

Heap

Recurly

Recurly

Zuora

Zuora

Cyfe

Cyfe

TransmogrifAI

TransmogrifAI

Image.

Music streaming services

According to the Music Streaming Market Size, Share & Trends Analysis Report, 2022-2030, the global music streaming market size was valued at USD 29.45 billion in 2021. Between 2022 and 2030, it is expected to grow at a CAGR of 14.7%. The growing use of digital platforms and smart devices is expected to boost the market growth. Music streaming services allow users to listen to audio and podcasts and watch music videos. Due to their features, these platforms are gaining popularity.

Music Streaming Market

Due to the popularity of music streaming platforms and the increasing disposable income of individuals, the market has grown rapidly. Also, streaming services are rapidly gaining popularity due to the availability of free trials and subscription options and the decline in CD sales.

Additionally, cloud-based music is gaining popularity in the market. Companies are working on developing apps that make streaming music easy on tablets and smartphones. By integrating a cloud component into music streaming platforms, companies can enhance their services by saving storage space and offering easy streaming from multiple devices. Factors such as the digitally literate population and smart devices fuel future market growth.

Spotify tech stack

In essence, all music streaming applications work similarly. Millions of tracks are stored either on physical servers or in clouds (Spotify chose the latter) and are then streamed to a user's device. 

But there's much more to Spotify. Pivotal to the music streaming giant's success is its functionality of music discovery based on complex algorithms of preference and behavior analysis. 

Spotify's tech stack focuses on three primary challenges:

  • Uninterrupted streaming: Multiple servers in different locations
  • Data storage: Own cloud-based architecture, Hub framework, Google Cloud, Docker, Apache Storm
  • AI-based recommendations: Python

Application and data technologies used to Spotify

Python Logo.

Python

NGINX

NGINX

Google Cloud Bigtable

Google Cloud Bigtable

Java

Java

PostgresSQL

PostgresSQL

Cassandra

Cassandra

Hadoop

Hadoop

Google Cloud

Google Cloud

Apache Storm

Apache Storm

BigQuery

Big Query

Bootstrap

Bootstrap

Amazon S3

Amazon S3

Amazon CloudFront

Amazon CloudFront

Kafka

Kafka

DevOps technologies used to Spotify

New Relic

New Relic

Percy

Percy

Docker

Docker

Datadog

Datadog

Solarwind Pingdom

Solarwind Pingdom

TestFlight

TestFlight

Apache CloudStack

Apache CloudStack

Helios by Spotify

Helios by Spotify

Business tools and utilities used to Spotify

AdRoll

AdRoll

Desk

Salesforce Desk

Qualaroo
Blossom
G Suite

G Suite

Google Analytics

Google Analytics

Twilio SendGrid

Twilio SendGrid

Optimizely

Optimizely

Google Cloud Dataflow

Google Cloud Dataflow

Lookback

Lookback

Hub Framework by Spotify

Hub Framework by Spotify

Pandora tech stack

Pandora is one of the oldest and most recognizable names in the streaming music category. It offers a relatively basic feature set and a few intriguing extras to help it compete with the big streaming music players. 

Founded in 2000 as Savage Beast Technologies, the company initially targeted B2B customers. In 2005, the company shifted its focus to the consumer market. 

In February 2019, Sirius XM Holdings acquired Pandora for $3.5 billion in stock. In 2021, Pandora had about 55.9 million active monthly users and 6.4 million subscribers.

In 2021, Pandora Music generated $2 billion in revenue, a 22% increase over the previous year. Pandora's market cap was $4.66 billion in October 2022. 

Music streaming service Pandora is 2nd most popular, with 43 sessions per user per month. This is only second to Spotify, with 61 monthly sessions per user. Spotify has almost 30% more sessions per user.

Application and data technologies used to Pandora

jQuery

jQuery

HTML5

HTML5

Python Logo.

Python

React

React

Java

Java

PostgresSQL

PostgresSQL

Apache HTTP Server

Apache HTTP Server

Redis

Redis

Sass

Sass

Swift

Swift

Backbone js

Backbone JS

Underscore

Underscore JS

Box

Box

DevOps technologies used to Pandora

Jenkins

Jenkins

Bitbucket

Bitbucket

Webpack

Webpack

TrackJS

TrackJS

Android

Android

Vagrant

Vagrant

TestFlight

TestFlight

Business tools and utilities used to Pandora

Slack

Slack

Jira

Jira

Fond (ex AnyPerk)

Fond (ex AnyPerk)

inVision

inVision

AdRoll

AdRoll

OneLogin

OneLogin

Google Analytics

Google Analytics

Twilio SendGrid

Twilio SendGrid

Oracle

Dyn by Oracle

AI sphere projects 

According to the Fortune Business Insights report, titled Artificial Intelligence Market Forecast, 2022-2029, is expected growing investment in AI technology by enterprises of all sizes across industries. Retail, BFSI, healthcare, food and beverage, automotive, and logistics are among the industries driving the demand for AI technology.

The Artificial Intelligence market size was valued at USD 328.34 billion in 2021. During the forecast period, the global AI market is expected to grow from USD 387.45 billion in 2022 to USD 1394.30 billion in 2029 at a CAGR of 20.1%.

It is becoming increasingly difficult to ignore the number of successful AI companies worth more than $1 billion, mainly since many of them were only founded within the last 5 years. Today exist, more than 117 AI unicorn companies.

Databricks tech stack

Databricks is a data lakehouse architecture and AI company. It provides a unified, open platform for all data. As well it is the first lakehouse platform in the cloud.

Currently, the value of this organization is $38 billion. In 2019, it became a tech unicorn thanks to investments from Andreessen Horowitz, BlackRock, CapitalG, Fidelity Investments, Microsoft, and Salesforce Ventures.

More than 5,000 of organizations worldwide — including Comcast, Condé Nast, Nationwide, H&M, and over 40% of the Fortune 500—rely on Databricks' unified data platform for data engineering, machine learning, and analytics. The Databricks platform provides data scientists, engineers, and analysts with a simple collaborative environment for running interactive and scheduled data analysis tasks.

Application and data technologies used to Databricks

Sass

Sass

Node JS

Node JS

JS

JS

Python Logo.

Python

HTML5

HTML5

Java

Java

CSS

CSS 3

PHP

PHP

C Logo

C

C++

C++

Scala

Scala

R Language

R Language

GraphQL

GraphQL

TypeScript

TypeScript

SQL

SQL

Jsonnet

Jsonnet

Splunk

Splunk

Spark

Spark

Amazon S3

Amazon S3

MySQL

MySQL

Cassandra

Cassandra

Hadoop

Hadoop

InfluxDB

InfluxDB

Kafka

Kafka

Azure Blob Storage

Azure Blob Storage

React

React

redux

Redux

DevOps technologies used to Databricks

Kubernetes

Kubernetes

Jenkins

Jenkins

Terraform

Terraform

Bazel

Bazel

Webpack

Webpack

Docker

Docker

Gulp

Gulp

Amazon EC2

Amazon EC2

Microsoft Azure

Microsoft Azure

Google Cloud

Google Cloud

Amazon Web Services

Amazon Web Services

New Relic

New Relic

CloudWatch

Amazon CloudWatch

Grafana

Grafana

AWS CloudTrail

AWS CloudTrail

Azure Monitor

Azure Monitor

AppDynamics

AppDynamics

Business tools and utilities used to Databricks

Tableau

Tableau

Salesforce

Salesforce

Google Analytics

Google Analytics

VWO

VWO

Databricks

Databricks

Okta

Okta

Zscaler

Zscaler

Smartling

Smartling

JAMF

JAMF

Workday

Workday

Greenhouse

Greenhouse

NetSuite

NetSuite

FinancialForce

FinancialForce

Entelo

Entelo

Microsoft Excel

Microsoft Excel

Kinsta

Kinsta

Pantheon

Pantheon

Marketo

Marketo

ServiceNow

ServiceNow

ByteDance (TikTok) tech stack

ByteDance was founded in March 2012 by Zhang Yiming, it became a tech unicorn in 2017. And it is best known for its mobile apps with entertainment value. Currently, ByteDance owns Douyin, Toutiao, TikTok, Xigua Video, Helo, Lark, and BytePlus. 

As of June 2021, ByteDance hosts 1.9 billion monthly active users across all its content platforms. A report by Reuters estimates the company's value at $78 billion and more than $7 billion in revenue for the first half of 2021.

In the framework of our article, we will consider Douyin, known as TikTok outside China. In 2018 ByteDance merged Musical.ly and TikTok and launched a new product in the U.S. Since then, the short-form video app has gained massive popularity. 

How does TikTok use AI? For example, the app includes an in-app text-to-image AI generator that lets users type a prompt and receive an image that can be used as a video background. Users can access the "AI greenscreen" effect through the short-form video app's camera screen.

TikTok's AI-driven algorithmic personalization took the "For You Page" (FYP) to an entirely new level. By connecting content creators and audiences based on commonalities, TikTok developed a symbiotic ecosystem. Using a two-pronged approach, it curated a personalized FYP to retain app user interest and boost influencer reach to reward them for creating valuable content.

The use of these techniques kept creators and viewers engaged and hooked on the app.

Application, data, and DevOps technologies used to TikTok

Swift

Swift

Kotlin

Kotlin

SQL

SQL

MongoDB

MongoDB

Cassandra

Cassandra

Node JS

Node JS

Alamofire

Alamofire

Azure Stream Analytics

Azure Stream Analytics

Amazon Web Services

Amazon Web Services

Amazon S3

Amazon S3

Amazon SES

Amazon SES

Amazon SNS

Amazon SNS

Google ML Kit

Google ML Kit

ARCore

ARCore

Twilio

Twilio

Google Cloud Messaging

Google Cloud Messaging

Apple Push Notifications

Apple Push Notifications

Fintech projects

The Global Fintech (financial technology) Market is valued at USD 112.5 Billion in 2021 and is projected to reach a value of USD 332.5 Billion by 2028. The Global Market is expected to grow to exhibit a CAGR of 19.8% over the forecast period.

Fintech uses new technical breakthroughs in financial products and services to enhance and automate the supply and usage of financial services. It also intends to compete with existing traditional financial methods in delivering financial services by incorporating various technologies such as application programming interfaces (APIs), artificial intelligence (AI), blockchain, and data analytics.

Revolut tech stack

Revolut is a UK-based financial technology company offering a range of financial services. The company was founded in 2015. 

The current valuation of this company is $33 billion due to investments from companies like Index Ventures, DST Global, and Ribbit Capital. With more than 1500 employees, it became a unicorn in 2018.

It became the UK's most valuable tech startup in 2021. Among the financial services offered by Revolut are current accounts, insurance, stock trading, debit cards, currency exchange, and foreign exchange.

Application and data technologies used to Revolut

JS

JavaScript

Python Logo.

Python

Node JS

Node JS

React

React

Java

Java

NGINX

NGINX

PostgresSQL

PostgresSQL

TypeScript

TypeScript

redux

Redux

Google Cloud

Google Cloud Platform

Swift

Swift

Kotlin

Kotlin

Scala

Scala

React

Create React App

jOOQ

jOOQ

Spark

Spark

DevOps technologies used to Revolut

Git

Git

Visual Studio

Visual Studio Code

Docker

Docker

IntelliJ IDEA

IntelliJ IDEA

Bitbucket

Bitbucket

New Relic

New Relic

Ansible

Ansible

ESLint

ESLint

Yarn

Yarn

Babel

Babel

WebStorm

WebStorm

Jest

Jest

Cypress

Cypress

Prettier

Prettier

TeamCity

TeamCity

Business tools and utilities used to Revolut

Gmail

Gmail

Slack

Slack

Jira

Jira

Confuence

Confluence

Figma

Figma

Gatsby

Gatsby

Klarna tech stack

Klarna, or Klarna Bank AB, is a fintech company founded in Stockholm, Sweden, in 2015. Buy now, pay later (BNPL) firm Klarna received a $46 billion price tag last year on a June funding round.

With a valuation of $45 billion, Klarna is one of the world's leading fintech companies. Unlike many corporations that remain on-prem, Klarna has moved to the cloud. Companies using Klarna Payments for Payment Processing include Microsoft Corporation, Target Corporation, Nike, Inc., Deutsche Bahn, Philips Electronics Nederland B.V.

Application and data technologies used to Klarna

GraphQL

GraphQL

AWS Lambda

AWS Lambda

JS

JS

Python Logo.

Python

Node JS

Node JS

React

React

Java

Java

TypeScript

TypeScript

Amazon EC2

Amazon EC2

React Native

React Native

Kafka

Kafka

Scala

Scala

Erlang

Erlang

DevOps technologies used to Klarna

Kubernetes

Kubernetes

Bitbucket

Bitbucket

Sentry

Sentry

CloudWatch

Amazon CloudWatch

AWS Elastic Load Balancing

AWS Elastic Load Balancing

Datadog

Datadog

Business tools and utilities used to Klarna

Slack

Slack

Jira

Jira

G Suite

G Suite

Confuence

Confuence

Stack Overflow

Stack Overflow

Internet software & services

The internet software and services industry is relatively small, primarily involved in providing platforms, networks, solutions, and services to online businesses, as well as facilitating customer interaction.  

The global business software and services market size was valued at USD 429.59 billion in 2021 and is expected to expand at a CAGR of 11.7% from 2022 to 2030. In retail, manufacturing, and healthcare industries, the growing volume of enterprise data and increased automation of business processes are driving market growth. Furthermore, the rapid deployment of enterprise software and services across IT infrastructure contributes to market growth by improving decision-making, reducing inventory costs, and improving profitability.

Canva tech stack

Canva is one of the most successful startups in Australia. It is an online graphic design platform designed to create beautiful documents. This platform offers drag-and-drop features and professional layouts to design consistently. Users can choose stunning graphics through a vast collection of professionally designed layouts to personalize the design with a stock library of photographs, illustrations, and imagery. Moreover, users can design presentations and social media graphics with appropriate layouts.

Canva was launched in 2013 by Melanie Perkins, Cliff Obrecht, and Cameron Adams. And today, it is one of the world's most valuable startups after raising $200 million in new funding at a $40 billion valuation.

Canva's already on a level few startups have reached. Among the Forbes Cloud 100 list of top private cloud companies, Canva is ranked second only to Stripe in terms of valuation. Over the years, Canva's sales have more than doubled, and it has become a profitable company with a positive cash flow helping over 55 million monthly active users across more than 190 countries. 

The company faces not only giants like Adobe (InDesign, Photoshop), Microsoft (PowerPoint), and Apple (Pages, Keynote) but also startups like Sketch, Figma, Easel.ly, Visual.ly, and Piktochart.

In the earlier days of Canva, the codebase comprised Java for the backend and Javascript on the front end. This approach worked well back then, but it would've been impossible to scale to the number of engineers they have now and remain productive if they hadn't adapted.

Application and data technologies used to Canva

JS

JS

React

React

Java

Java

TypeScript

TypeScript

Amazon EC2

Amazon EC2

Amazon CloudFront

Amazon CloudFront

Storybook

Storybook

MobX

MobX

Jetty

Jetty

DevOps technologies used to Canva

Git

Git

Webpack

Webpack

New Relic

New Relic

Rollbar

Rollbar

Percy

Percy

Business tools and utilities used to Canva

Mailgun

Mailgun

Mandrill

Mandrill

Slack

Slack

G Suite

G Suite

Google Analytics

Google Analytics

Mixpanel

Mixpanel

Optimizely

Optimizely

Segment

Segment

Miro tech stack

In 2011, Andrey Khusid and Oleg Shardin founded RealtimeBoard, which they rebranded as Miro in 2019. Miro is a cloud-based visual collaboration platform designed to work among teams of all kinds. This solution includes a digital whiteboard for research, ideation, building customer journeys and user story maps, wireframing, and other collaborative activities. Today over 30 million users worldwide use this platform.

Miro runs in a web browser or in the Miro apps. Besides macOS and Windows, there are apps for Android, iOS, and Microsoft mobile devices.

Miro handles storage for all accounts. Currently, there is no option to bring your own cloud storage.

On Jan 5, 2022, the company announced its most significant round to date, $400 million in a Series C, propelling its valuation to $17.5 billion. Since Miro was founded, a new capital infusion has given $476 million in total funding. Thirteen investors fund Miro. Julien Codorniou and Atlassian are the most recent investors. It has a post-money valuation in the range of $10B+ as of Jan 5, 2022, according to PrivCo.

Application and data technologies used to Miro

JS

JS

Node JS

Node JS

React

React

Java

Java

PostgreSQL

PostgreSQL

TypeScript

TypeScript

Angular

Angular

Redis

Redis

Amazon S3

Amazon S3

Amazon EC2

Amazon EC2

React Native

React Native

Spring Boot

Spring Boot

Kotlin

Kotlin

Linux

Linux

Less

Less

Hazelcast

Hazelcast

DevOps technologies used to Miro

GitHub

GitHub

Git

Git

Docker

Docker

Kubernetes

Kubernetes

Bitbucket

Bitbucket

Webpack

Webpack

Mockito

Mockito

Bamboo

Bamboo

JUnit

TestNG from JUnit

Business tools used to Miro

Slack

Slack

Jira

Jira

Confuence

Confuence

Uber tech stack

Uber initially took an innovative approach: they opted to break the then mainstream monolithic architecture into many independent elements so that scaling (as well as a wide variety of fixes and improvements to the application) is as painless as possible. 

Infrastructure and data storage are probably among the most vital elements of Uber's application as there's a huge need to work with maps, vehicles, and users on a per-location basis. The company chooses a hybrid cloud model that relies on a multitude of service providers, tools, and backup servers which get swapped out if and when the need arises. 

Docker and Mesos are used to run and scale the hundreds of microservices that the tech giant's app relies on. There's also a custom-built library of builds that's been converted into Docker images. 

Originally kicking things at the lower levels with Python and Node.JS, Uber has expanded to Java and Go for their higher performance and open-source ecosystem. Also, Go's native asynchronous programming gives the team a better grasp over the Python-based microservices once they are broken down.

Application and data technologies used to Uber

Python Logo.

Python

Java

Java

Golang Logo.

Golang

C Logo

C

C++

C++

HA Proxy

HA Proxy

Node JS

Node JS

jQuery

jQuery

React

React

MySQL

MySQL

NGINX

NGINX

PostgresSQL

PostgresSQL

MongoDB

MongoDB

Redis

Redis

Amazon EC2

Amazon EC2

Kafka

Kafka

Swift

Swift

Objective-C

Objective-C

Backbone js

Backbone.js

Cassandra

Cassandra

Spark

Spark

Hadoop

Hadoop

Apache Thrift

Thrift

RIBs

RIBs

AresDB

AresDB

DevOps technologies used to Uber

Grafana

Grafana

Sentry

Sentry

RequireJS

RequireJS

Prometheus

Prometheus

Puppet Labs

Puppet Labs

Nagios

Nagios

ZooKeeper

Apache Zookeeper

Graphite

Graphite

Jaeger

Jaeger

Brunch

Brunch

Peloton

Peloton

M3

M3

Uberalls

Uberalls

Kraken by Uber

Kraken by Uber

Business tools and utilities used to Uber

G Suite

G Suite

Asana

Asana

Zendesk

Zendesk

iDoneThis

iDoneThis

Mattermost

Mattermost

OneLogin

OneLogin

Delighted

Delighted

Google Analytics

Google Analytics

Elasticsearch

Elasticsearch

PayPal

PayPal

Twilio

Twilio

Twilio SendGrid

Twilio SendGrid

Mixpanel

Mixpanel

Optimizely

Optimizely

TensorFlow

TensorFlow

Crazy Egg

Crazy Egg

Heap

Heap

Braintree

Braintree

HackerOne

HackerOne

Ludwig

Ludwig by Uber

Lyft tech stack

As any Taxi service, Lyft has built its tech stack around three pillars: simplicity, great UI\UX, and excellent geolocation. 

In terms of the architecture, Lyft and Uber are similar, too: both aggregators are built using scalable microservices. The choice of Python, Java, and Go seems obvious. 

Lyft is heavily relying on various cloud and data storage solutions. But none are set in stone: the company only uses third-party services as long as those are cheaper than in-house storage and servers.

Application and data technologies used to Lyft

React

React

MongoDB

MongoDB

NGINX

NGINX

PHP

PHP

Python Logo.

Python

Cloudflare

Cloudflare

Amazon Web Services

Amazon Web Services

Dropbox

Dropbox

Golang Logo.

Go

Swift

Swift

MongoLab

MongoLab

Java

Java

Flask

Flask

Angular

Angular

Business tools and utilities used to Lyft

Slack

Slack

Jira

Jira

Confuence

Confuence

G Suite

G Suite

HelloSign

HelloSign

Medium

Medium

Git

Git

Jenkins

Jenkins

GitHub

GitHub

Vim

Vim

PyCharm

PyCharm

Sublime Text

Sublime Text

VirtualBox

VirtualBox

Atom

Atom

Xcode

Xcode

Sauce Labs

Sauce Labs

Image.

Airbnb tech stack

With over 150 million active users, Airbnb is rightfully the king of the booking scene. How have they achieved it? There are two main answers: amazing filters functionality and great suggestions algorithms. 

The entire application is built around a sophisticated, AI-powered algorithm that finds relevant rooms and accommodation according to a user's requirements. The app considers countless factors: for example, ratings, experience, and proximity to eateries or public transportation joints. 

The recent COVID pandemic has made travel much harder for everyone, but Airbnb is more than ready to handle the increased load when the travel limitations are gone. The reason is that it's not a cloud-based application, so they are ready to scale whenever there's a rise in demand.

Application and data technologies used to Airbnb

JS

JS

React

React

NGINX

NGINX

Java

Java

MySQL

MySQL

Redis

Redis

Sass

Sass

Ruby

Ruby

Amazon

Amazon Web Services

Hadoop

Hadoop

Druid

Druid

Airpal

Airpal by Airbnb

DevOps technologies used to Airbnb

GitHub

GitHub

Webpack

Webpack

Kibana

Kibana

New Relic

New Relic

Sentry

Sentry

Jest

Jest

Airbnb SmartStack

Airbnb SmartStack

Chef

Chef

CloudWatch

Amazon CloudWatch

Logstash

Logstash

Vagrant

Vagrant

Datadog

Datadog

Enzyme

Enzyme

Business tools and utilities used to Airbnb

Slack

Slack

Asana

Asana

G Suite

G Suite

inVision

inVision

Assemblage

Assemblage

Campaign Monitor

Campaign Monitor

React Sketch app

React Sketch.app

Google Analytics

Google Analytics

Twilio

Twilio

Mixpanel

Mixpanel

Nexmo

Nexmo

Twilio SendGrid

Twilio SendGrid

Braintree

Braintree

Amazon Route 53

Amazon Route 53

Wingify

Wingify

Superset

Superset

Lottie
Urban Airship

Urban Airship

Image.

In conclusion

Putting together the right tech stack is a continuous challenge, and one of the ways to succeed in it is to turn to industry's biggest players. Seeing what they are choosing can give you clues as to what your own project needs. And researching the logic behind their choices can help you make better tech stack decisions. If you are at a loss with the choice of technologies for developing your project, you can easily contact us by filling out the form. The consultation is free. During the first consultation, we will discuss the idea of the project and set goals, needs and ideas. After this call, we will pick a team of specialists.

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