Node.js vs Java - Understanding the Difference Between Them

There are many backend technologies available today, but out of these, two technologies have emerged as popular choices amongst developers worldwide, Node.js and Java. While both technologies offer powerful solutions for building server-side applications, there are notable differences in their performance, architecture, and use cases. 
In this article, we will compare these two backend tech stacks, highlighting their strengths and exploring their unique use cases.
Benefits of Node.js and its use cases
Node.js has been built on Google’s V8 JavaScript engine and is an open-source, cross-platform that allows developers to execute JavaScript outside a web browser. It's a commonly used tool that enables developers to build applications that can work with modern web app frameworks and server-side scripting. 
Benefits of using Node.js
• Performance: Applications built on Node.js offer high performance, as it compiles JavaScript into machine code, which makes it fast and efficient. This enables Node.js to run multiple simultaneous connections which makes it extremely scalable. This is very beneficial for real-time applications where quick responses are critical, such as in chat rooms or the use of collaborative tools. Node.js is efficient and lightweight and makes handling data-intensive, real-time applications across distributed devices easy.
• Scalability: Node.js can manage multiple connections simultaneously using an event-driven, non-blocking I/O model that allows it to scale as the workload increases. This makes it very useful for applications that need to scale to handle increasing traffic loads. Node.js also allows horizontal and vertical scaling, which allows load distribution across multiple cores and machines. This capacity to scale offers improved resource management, better performance, and enhanced capacity to handle higher volumes of client requests. 
• Full stack: Developers using Node.js can write both the front and back-end code using JavaScript, which leads to a more streamlined and efficient development process. The uniformity of language increases productivity, allows code sharing, reuse, and increases knowledge sharing. 
• Node package manager: The Node Package Manager (NPM) is a standard package manager for Node.js and provides several benefits to developers. It is one of the largest storage for a single language with over 2.1 million listed packages. It allows developers to install and manage the dependencies of projects using a package.json file. Developers can also specify any particular version using its versioning feature. Since this is an open-source environment, the community, publishing, and sharing of open-source Node.js libraries is encouraged, which increases the ecosystem.
Node.Js Use Cases
• Netflix: Netflix uses Node.js for its scalability feature that allows Netflix to stream high volumes to its millions of subscribers. Netflix developed NodeQuark, a tool that allows them to authenticate and route requests. It also moved its APIs from Groovy Scripts to Node.js versions for various platforms like mobile, TV, laptop, etc. 
• Uber: Uber solved its data handling problems using Node.js which was quick and scalable and made it relatively easy to manage large volumes of notifications and other requests. Uber used Node.js to develop its matching system.
Benefits of Java and its use cases
Java is an object-oriented programming language and compiled Java code can be run on any platform that supports Java without developers recompiling the code. Java is known for its security, simplicity, and robustness and is used for creating applications for all major platforms. 
Benefits of using Java
• Performance: Applications developed using Java are compiled into bytecode, which is then compiled into machine code using the Java Virtual Machine (JVM). This makes applications fast and efficient and enables Java to handle multiple threads, making it scalable. This multi-threading model makes Java more suitable for data-intensive applications.
• Scalability: Java is more suitable for data-intensive applications as it uses a multi-threading model. Java achieves scaling in two different ways, vertical scaling, which involves increasing server resources such as RAM, disk space, processors, etc., or horizontal scaling, which is achieved by adding more machines or additional nodes, also called clustering. But these scenarios can be more expensive.
• Automatic memory management: Automatic memory management is managed by Java Virtual Machine and does not require any specific process to achieve it. A system called a garbage collector is used for automatic memory management which ensures that any unused space is cleaned and memory is freed when it is not needed. This reduces or prevents memory leaks. The main benefit of automatic memory management is that it helps simplify code writing.
• Multithreading: Multithreading allows simultaneous execution of more than two parts of a program, maximizing CPU utilization. Parts of the program are called threads and are lightweight processes. Multithreading enables multitasking and it makes a more efficient use of the system resources to improve application performance. 
Java use cases
• Twitter: Twitter has used Java to develop Android apps and to streamline its usage. Much of Twitter’s code has been moved to the Java Virtual Machine (JVM) for performance and efficiency enhancement. 
• Spotify: Spotify Web API Java, a Java client is used by developers to interact with Spotify’s Web API using Java, which for example, allows it to control Spotify’s audio playback.
Final Words
Both Node.js and Java offer unique benefits to developers. Java with its extensive libraries and robustness is often used for large-scale and enterprise-level applications, whereas Node.js offers an efficient and lightweight solution for real-time applications and microservices. While the applications of Java or Node.js depend on specific requirements, custom node.js web application development services can provide specific solutions that can be used to develop complex real-time, data-heavy applications.