Amazon, Airbnb, IBM, Netflix, Microsoft, PayPal, and Salesforce – these are only some of the major organizations using Java in their popular applications. Then there are banks and financial institutions using Java that are far too many to count! What makes it such a popular choice for all of them?

Enterprises are drawn to stable and trustworthy technologies that will provide them with peace of mind over many years of growth. Backed by Oracle, and supported by a big community, secure, and backward compatibility with previous versions are all highly prized by large businesses.

Big data is all about the three Vs – volume, velocity, and variety. A great amount of data, the rate at which it is received, and the sheer diversity of it are an everyday reality not only for enterprises such as Amazon or IBM but also for a host of successful startups. Java, yet again, is at the forefront of it all.

In fact, popular data storage and processing platforms such as Hadoop HDFS were written in Java. The language also supports various data sciences techniques, while being much more versatile than other big data languages such as R.

In today’s interconnected world every device and platform is yet another channel for a business to explore. The Internet of Things market is worth more than $500 billion and will grow in the coming years. Want a piece of that pie? Then, you might need some Java developers.

When it comes to IoT apps, Java is widely used in embedded development due to its portability which stems from the WORA principle. Its multithreading provides excellent performance and scalability, and it also goes a long way to address one of the main challenges of IoT technologies – security.

Some people have only woken up to the power of AI when the latest version of ChatGPT hits the shelves. Others had already been at the forefront of this innovation for a while by then. And this interest is often associated with Java – developers at Amazon or Microsoft could tell you a thing or two about it.

Java supports concurrent programming, making it a sound choice for apps that require parallel processing. This includes various data analytics apps, among others. Java is also equipped with all kinds of machine learning libraries such as Apache Jena for building the semantic web, the Eye reasoning engine, or Neuroph for neural network creation.

Both AI and big data apps often process large volumes of incoming data. To handle the intensity, they often turn to stream processing. This technique allows for the continuous processing of large streams of data in real-time instead of collecting it firstly, as is the case with batch processing.

Some use cases for stream processing include stock market analysis, geospatial data processing, or production line monitoring. They are likely to use Java because, other than its support for data science techniques, it is also supported by top data streaming platforms such as Apache Kafka.