Which technology is used in LinkedIn?
LinkedIn has been around for a long time now – it began as an online resume database back in 2003. Since then, there have only been minor changes to its tech stack. It’s still using PHP on the front-end, but behind the scenes, they use many different languages for their various parts. The following article will explain which technologies LinkedIn uses across all layers of their infrastructure.
In this article, we'll be focusing on the core components of LinkedIn's software stack and how it evolved from its original state. We're not going to cover everything here, instead we'll focus on the most important pieces of LinkedIn's infrastructure. This way you can get acquainted with the inner workings of LinkedIn without having to dive deep into every single piece of code. You may notice that these names don't always match up with the official ones used by LinkedIn. That's because those are the actual names that LinkedIn developers use internally when discussing them.
If you want to learn more about each specific component, check out our list of articles covering the complete LinkedIn tech stack. In addition, if you'd like to know more about the history of LinkedIn, read our guide on how Linkedln came to life. If you want to understand why LinkedIn exists at all, check out our article explaining why people share so much information through social media sites. And finally, if you want to see how LinkedIn works, watch our video tour of its internal network!
Does LinkedIn use Java?
Yes, LinkedIn does indeed use Java. Before 2013, LinkedIn ran exclusively on J2EE and SQL databases. After Oracle bought Sun Microsystems, they decided to switch to OpenJDK 6. In 2015, LinkedIn migrated to Java 8 and adopted Spring Framework 4.1.0. This move brought many new features including support for reactive programming via RxJava. However, after migrating to Java 9, LinkedIn realized that they needed even better performance, so they switched to Netty 3.5.0. Nowadays, the majority of LinkedIn’s codebase runs natively on top of Java 11.
So far, we've covered the major players that make up LinkedIn's modern web application. Next, let's talk about how LinkedIn handles data storage.
What is LinkedIn website made with?
LinkedIn uses three kinds of servers:
The first kind is Elasticsearch, which is a distributed search engine designed specifically for large scale applications. At the moment, it supports more than 1 billion documents and millions of users.
The second type of server is Apache Cassandra, which is a NoSQL database based on the C* protocol. It provides high availability, scalability, fault tolerance, and real-time updates.
Finally, the third type of server is MongoDB, which is another open source document store similar to CouchDb or DynamoDB.
All of these servers run on Linux operating systems.
Is Google written in Java?
No, Google isn't written in Java. Instead, it relies heavily upon the Java Virtual Machine (JVM). There aren't any Google apps written in Java though, since Java doesn't provide enough flexibility. For example, while Java allows you to write object-oriented programs, it lacks polymorphism (which means you cannot create subclasses of objects in Java).
Since Google has no need for flexible classes, it relies solely on static typing. This makes writing code easier and faster, especially when dealing with lots of small files. Another reason for this choice is that Java is much slower than compiled languages such as C++ and Fortran. So, if you compare Google's development speed against that of Microsoft, you won't find any significant difference between the two companies.
Another thing to keep in mind is that Java offers very limited memory management capabilities compared to C++ and Fortran. Thus, you might experience unexpected crashes due to running low on RAM. Thankfully, Google solves this issue by deploying multiple instances of Java processes per user.
Is Netflix coded in Java?
Netflix developed its own streaming service called Qwikster. When it went live, Netflix already had a few years worth of content stored inside Amazon S3. Unfortunately, the company struggled to maintain compatibility with DVD rentals. To fix this problem, Netflix wanted to implement a new system where customers could rent DVDs and Blu-rays directly from Netflix. In order to do this, Netflix needed a robust file sharing solution. Hence, they chose Java.
After launching Qwikster, Netflix eventually returned to AWS and built a new streaming service called Instant Watch. With this change, Netflix completely abandoned Java and moved to Scala.
Is Netflix coded in Java?
No, Netflix isn't written in Java. As previously stated, Netflix used Java temporarily until it discovered Scala.
Now that you know which platforms LinkedIn has available to build its products, let's look at what they actually use.
Yes, LinkedIn uses React for building their websites. Although LinkedIn initially used Angular 2, they later replaced it with React. Why did they decide to go with React? One of the main reasons was that Angular 2 wasn't compatible with mobile devices yet, so LinkedIn didn't feel comfortable relying on Angular 2's mobile version.
However, LinkedIn's decision to replace Angular 2 with React was mostly driven by cost savings. According to LinkedIn, switching to React would save $10 million annually. On the flipside, switching to Angular 2 wouldn't add anything new to LinkedIn, as it already supported both desktop browsers and mobile devices.
Moreover, LinkedIn also found React to be easier to work with and less error prone. Lastly, LinkedIn felt that React offered better developer productivity.
What is LinkedIn’s backend framework?
Linkedin originally relied on the LAMP stack. Today, however, it mainly utilizes NGINX and MariaDB.
NGINX is an HTTP server that acts as a reverse proxy, load balancer, caching server, and HTTPS accelerator. In addition to handling traffic requests, it also serves static assets and compiles templates.
MariaDB is an open source relational database management system (RDBMS) derived from the Berkeley DB project. Its primary goal is to offer ACID transactions, multiuser access control, and easy replication.
It should be noted that despite being a commercial product, MariaDB comes with free versions of its client and plugin APIs.
How was LinkedIn built?
When LinkedIn launched, it consisted of five separate websites. These included:
- People Search - This section provided job listings and resumes.
- Profile Search - This page allowed members to view profiles created by others.
- Jobs - This part displayed jobs posted by recruiters and employers.
- Groups - Members were able to join groups and communicate with group leaders.
- Talent Solutions - This site provided career advice and guidance.
Over the past decade, LinkedIn has expanded rapidly. Today, there are nearly 600 million active registered users who generate roughly 300 billion monthly connections.
To learn more about how LinkedIn grew from a simple resume database to one of the world's biggest professional networks, follow along with our detailed timeline.
LinkedIn has been one of the most influential social platforms since its inception. It started as a free online tool to help professionals connect with each other but soon evolved into an important business tool for anyone who wants to network or find new job opportunities. The site now boasts over 500 million members around the world.
Although it might have changed a lot during the years, LinkedIn still follows the same basic principles as when it first came out. Its primary goal remains helping people build professional relationships by connecting them through their common interests. This helps you discover potential connections both within your industry and outside of it. You can also look at LinkedIn as a great way to learn more about different companies and industries. In fact, there are many articles on this website dedicated solely to explaining why you should be using LinkedIn for whatever purpose you want.
However, even though LinkedIn offers so much value to users like us, we’ve never really thought too deeply about how exactly they do all these things. We know LinkedIn runs behind the scenes, which means that if we wanted to create our own version of LinkedIn (or any similar service) from scratch, we would need to understand how it works. So let’s take a closer look at how LinkedIn actually does work!
If you’re anything like me, then you probably don’t spend time thinking about the tech stack underneath every major company or app you use. However, I guarantee that you will start wondering about the underlying software and hardware once you realize that the whole internet relies on servers, databases, APIs, and languages. Even though you may not pay attention to those details, they play a huge role in determining whether or not something succeeds or fails. For example, if you’re building a dating application, you must consider everything from server load capacity to user experience before you launch your product.
So without further ado, here are some interesting facts about the technology used by LinkedIn.
What is LinkedIn programmed in?
The main reason why LinkedIn developers choose to code in such diverse languages is because they believe that it allows them to write better code faster. If they had chosen to only develop in a single language, they would likely end up writing less efficient solutions that could cause performance issues down the line.
Furthermore, if you were looking at developing another version of LinkedIn yourself, you would need to make sure that the code you wrote would run consistently across multiple devices. That’s where the choice between functional and object oriented programming comes in handy. Functional programming focuses primarily on solving problems rather than manipulating data structures like objects. As a result, it tends to perform well under stress. Object orientation, however, requires programmers to think about how individual pieces of information fit together, making it easier to scale across various environments.
When it comes to choosing between two equally good options, it usually depends on personal preference. But for the sake of argument, let’s assume that you decided to go with functional programming. What kind of infrastructure would you need in order to support thousands of concurrent users? Would you ever need to deal with scaling issues? How easy would it be to migrate away from your current provider? And finally, how fast would the system become outdated? All of these questions depend heavily on the type of programming language you chose.
For instance, if you went with Java instead of functional programming, you wouldn't have to worry about scaling issues because Java takes care of threading automatically when you're dealing with multithreaded applications. On top of that, you'd get access to libraries written in Java that provide functionality beyond what you would normally come across with regular coding practices.
Another thing to keep in mind is that while LinkedIn is based off of Microsoft Azure, it doesn't mean that the entire back-end is done in.NET. Indeed, the front end is developed in React Native, Angular 2+, and Polymer, whereas the backend is mostly made up of NodeJS, Express, MongoDB, Redis, Elasticsearch, AWS Lambda, Cloudfront, S3, DynamoDB, and Kinesis.
As far as performance goes, LinkedIn claims that it processes 1 billion requests per day, which translates to roughly 3 terabytes of traffic processed daily. Furthermore, the average response time ranges somewhere between 4 milliseconds and 10 seconds depending on the location of a particular request. To put that number into perspective, Facebook handled approximately 200 petabytes of data per month last year.
Now that you know more about how LinkedIn operates, it shouldn't surprise you that the majority of its features revolve around the idea of sharing content. Since the core function of LinkedIn revolves around finding connections, it makes sense that the bulk of its services focus on that specific area.
What technologies are used in LinkedIn?
While LinkedIn itself isn’t open source, there are quite a few projects that leverage its API. Here is a brief overview of the most notable ones:
Pulse - Pulse is a news aggregator that pulls stories from Twitter, Reddit, Hacker News, Digg, Quora, and Facebook and displays them chronologically according to relevance. There are plans to add additional sources later on.
Linkedin Data Extractors - Linkedin Data Extractors allow you to import data directly from LinkedIn into Excel or CSV files. They currently cover four categories: Companies, Jobs, People, and Events.
LinkedIn Insightly Dashboard - A simple dashboard that shows metrics related to engagement, posts, followers, shares, etc.
Opinion and Activity Explorer - An opinion explorer that lets you explore public opinions about topics like sports teams, movies, books, music, etc. Meanwhile, activity explorer provides stats related to likes, comments, reposts, shares, etc.
LinkedIn Search Engine - A search engine that indexes LinkedIn profiles, groups, jobs, events, companies, tags, images, videos, and media.
LinkedIn Feed Reader - A feed reader that enables you to read updates about your contacts and follow relevant feeds.
LinkedIn Job Board - A job board that connects candidates and employers via a custom API.
LinkedIn GraphQL Playground - A playground for experimenting with graphql queries against Linkedin’s database.
LinkedIn Developer Toolkit - A set of tools that enable developers to integrate LinkedIn into their apps/websites.
In terms of operating systems, LinkedIn supports Windows, macOS, Linux, Android, iOS, and Chrome OS.
Do you remember the term “backends” mentioned earlier? Well, LinkedIn’s backend consists of several components including a message broker, a caching layer, a logging component, a distributed storage solution, and a queue management system.
Finally, one of the coolest parts of LinkedIn is that it also powers mobile apps for iPhone and Android. Not only does it offer native apps that let you view profile info and send messages, it also offers a third party developer kit that allows you to customize the interface.
Lastly, if you want to see what LinkedIn looks like on desktop, check out these screenshots taken from my colleague's blog:
Does Google use C++?
No, Google doesn’t use C++. Instead, it uses TypeScript, Flow, Closure Compiler, Traceur, and Babel to compile and transpile its codebase. In addition to compiling the code, these tools also handle syntax errors and warnings, lint the project, generate documentation, and test the code base.
All told, it sounds like a pretty extensive setup. Thankfully, none of those steps require you to manually maintain the codebase. Instead, they automate the process completely. When it comes to running tests, Travis CI handles testing unit-, integration-, and acceptance-tests. Google Bot analyzes the codebase in real-time, while SonarQube ensures quality throughout the lifecycle of the project.
There are plenty of benefits to having automated builds. First, the speedier turnaround times allow engineers to move onto bigger tasks sooner. Second, the ability to detect bugs early prevents costly mistakes and wasted resources. Finally, automated builds eliminate human error altogether and ensure consistent results regardless of the environment.
With all of these tools, it becomes clear that LinkedIn employs a robust engineering team and has invested significant amounts of money into creating a reliable and scalable infrastructure. Although it's impossible to tell how successful LinkedIn will ultimately turn out to be, it's safe to say that they've created a solid foundation upon which future growth can occur.
LinkedIn has been around for over 20 years now. It began as a professional networking site with only 500 members back in 2004. Now it’s one of the biggest platforms to connect people from all walks of life. The company employs over 13 million employees worldwide and manages billions of connections between users every day.
The tech stack behind this massive network is impressive, but not everyone knows exactly which technologies they use. Let’s take an inside look at the different components of their infrastructure so you can learn where your favorite platforms come from!
If you want to get started using LinkedIn, check out our guide on getting connected.
Is YouTube written in Python?
YouTube is probably one of the most popular video sharing sites online today. There are millions of videos uploaded each month by amateur filmmakers who upload everything from music clips to documentaries. And while YouTube does have its own programming language called C++, many other companies also leverage YouTube’s API (application program interface) to create their own websites or applications. In fact, according to Gartner research, 65 percent of enterprise businesses rely on APIs.
Most of these apps are made possible through the use of Python, a scripting language that allows developers to write code quickly without having to worry about syntax errors like those found in other languages such as Java or C#. Because Python is easy to read and simple to understand, it provides a great environment for beginners looking to start coding. If you want to know more about Python’s history, check out our article explaining why Python is awesome.
Is PHP still used?
While Python is often used to make web-based applications, the language itself isn’t always enough. To ensure compatibility across browsers and devices, programmers need to embed HTML into the application to display data properly. This means that if there’s a problem with the server, the entire website might be affected. Fortunately, PHP solves this issue by providing a way to generate dynamic content based on input received from clients.
PHP originated in 1995 when Rasmus Lerdorf created it as part of his work for the Swedish National Institute for Computer Science. Since then, PHP has grown to become one of the world’s most widely used open source programs thanks to its ease of development and flexibility. With nearly half of the top 10 million websites relying on PHP, it’s no surprise that it continues to power major projects including WordPress, Drupal, Magento, and Joomla.
What is Facebook coded?
Facebook is another big player in the social media industry. While Twitter relies heavily on hashtags and Instagram focuses on filters, Facebook offers its users something unique: news feeds. When you log onto the site, you see posts from friends and family along with interesting articles from publications both local and global. You can even add comments yourself!
But did you notice how much time you spend scrolling down Facebook’s timeline? That’s because unlike Twitter, Facebook doesn’t offer anything else except for status updates. Luckily, Facebook has a robust backend system that handles all of the heavy lifting. This includes things like maintaining user profiles, storing photos, creating groups, sending messages, managing likes, and organizing events.
Another common choice among developers is Node.js, which is typically paired up with Express, a lightweight framework that lets you build full fledged servers right within your browser. Node.js is extremely flexible and powerful, making it ideal for tasks such as realtime communication between multiple clients and running background processes.
You may already know that Microsoft invented ASP.NET MVC, a set of guidelines that allow developers to easily develop responsive websites. But did you realize that Visual Studio Code is also powered by ASP.NET? Although it’s just a text editor, it supports features such as debugging, version control, remote deployment, and Git integration that makes it easier than ever before for coders to collaborate.
Is LinkedIn written in Java?
Although the list above covers the various programming languages and platforms currently being utilized by LinkedIn, there are plenty of others that aren't listed here. These include Adobe Flash, Hadoop, MongoDB, Apache Cassandra, Neo4j, R, D3, PostgreSQL, Solr, Varnish, Spark, Flume, RabbitMQ, Akka, Spring Framework, ElasticSearch, and Kafka.
In reality, developers don’t usually stick to one specific language or technology. Instead, they tend to mix and match pieces together depending on what needs to be done. For example, many modern applications utilize microservices architectures that combine services written in different languages, enabling teams to tackle separate problems simultaneously.
By taking a closer look at LinkedIn’s tech stack, you should now be able to better understand how certain technologies came to play a role in the creation of this mammoth organization.