While Java is frequently used and has kept up with the latest trends in tech innovation, its future and longevity is speculated each year. Larisa Bugnar, Lead Software Engineer at EPAM Systems, Inc, explores the evolution, future, and adaptability of Java during Bucharest Tech Week ahead of EPAM’s presentation on the Java stage.
Among all programmers worldwide, approximately 35% are Java developers. Long-term support versions and a passionate community have highly contributed to Java’s success over the years. Not only did it focus on providing stable versions, but it has looked at future challenges and continuously provided options for cloud, big data, AI, and IoT to facilitate the development of applications.
Are you going Cloud?
Java is a robust, widely used platform-independent language and one of the best options for cloud solutions. It provides a framework that helps clients feel more confident about cloud security. Java security APIs include authentication, access control, cryptography, public key infrastructure, and secure communication.
From the beginning, Java has been an option in serverless architecture. It is easy to learn and widely used among all major cloud players (AWS, Azure and Google Cloud) to offer support for Java in their software development kits (SDKs). Java imposed itself in the microservices world by providing frameworks to shorten development time and provide reliable solutions for security, service discovery, data management, observability, testing and more. In the top 10 microservices frameworks, SpringBoot with Spring Cloud is the first alternative to consider. There are a variety of options for microservices frameworks to work with Java, including the following:
Vert.x by Eclipse foundation
Helidon by Oracle
Micronaut by Grails developers
Lagom for reactive microservices
AxonIQ is suitable for domain-driven design
Ballerina integrates with Java
Is Java Big Data?
Cloud has also brought big data closer to data scientists by providing tools to easily interact with large volumes of data without worrying about the infrastructure.
In the technology era, companies spend considerable resources on gathering information and analysing user behaviour. The main concern is to capture terabytes of data, corelate the information and visualize the results in a business-oriented manner. Predictions and informed decisions are taken based on the manipulation of large samples.
Java is a top option when it comes to big data, particularly because open source tools (Hadoop, Spark, Mahout) easily integrate with it. It comes as no surprise that Java is third among the top programming languages for data scientists in 2022.
Important elements of big data technologies have been written in Java (Apache Hadoop, Apache Hive, Apache HBase, Apache Cassandra). Java provides integration with ETL applications (Apache Camel, Apatar, Apache Kafka) to extract, transform and load data.
Afraid of AI?
In 2019, Forbes published an article about the fear of AI (Artificial Intelligence) and its unknown potential. Despite this, AI is rapidly advancing and becoming an integral part of today’s reality.
Should Java developers fear AI? From a Java perspective, there is nothing to fear. As a top player, Java is competing with Python and R to become the most popular language used in AI.
Whether it is machine learning (ML), artificial neural networks, genetic algorithms, or search algorithms, Java offers libraries and frameworks for AI programming such as:
Deeplearning4j –JVM library for neural network creation
RapidMiner – for machine learning algorithms
Apache OpenNLP - for processing of natural language text
Jenetics – for advanced genetic algorithm
Watchmaker – framework for genetic algorithms
JGAP (Java Genetic Algorithms Package) – component for genetic programming
Compared to its competitors Python and R, Java is widely used for enterprise applications and offers solutions in terms of security, multithreading, and rich APIs to deal with database interactions, networking, I/O etc. Due to its object-oriented nature, robust virtual machine, fast learning curve and active community Java has a 37.8% adoption rate in AI and ML according to Oracle’s survey from December 2021.
IoT – Internet of Things
Internet of Things refers to the possibility of making devices communicate with each other over the Internet.
IoT involves network communication, collecting data from sensors, analysing, and extracting valuable information, AI algorithms, and integration with devices and platforms.
Despite its powerful competitors such as C/C++ or Python, Java is one of the most popular programming languages used in IoT. “Write once, run everywhere” is a famous Java principle used to describe its popularity. This is important because IoT is about many different “things” capable of working together.
Moreover, Java offers a stable ecosystem and faces security and scalability challenges. Extensive APIs are provided to address any concurrency, connectivity, or networking issues. Hence its capabilities, Java is widely adopted in the IoT world.
Java learns from its mistakes and grows stronger. NullPointerException was the most common exception which led to billions of production issues. The code became more reliable after Optional was adopted and because of its flaws, new languages evolved from it. Thanks to its active community and open source mindset, the Java platform became the starting point of other languages like Scala (object-oriented but functional) or Kotlin (no more NPE ever). Even Go was created having in mind Java’s need to improve on memory management and run faster.
Although it’s impossible to predict the future, Java seems to find its place in evolving trends from big data to cloud, AI, and IoT. With all the new developments happening in Java, it’s safe to say that this programming language will remain an important player in the tech world.
Join us on 17 June at Bucharest Tech Week on the Java Stage to learn how to set up your Java application to work (read/update/delete content) with Google Docs using Google Docs. Daniel Brumusescu, Lead Java Software Engineer at EPAM will share ideas to drive REST APIs, types of requests, insert/delete text, format paragraphs/texts, work with tables, structure and elements of a document.