Java Trends and Technologies: Updates for 2022
Tech Insights
Java Trends and Technologies: Updates for 2022
Java Trends and Technologies: Updates for 2022
Tech Insights

Java Trends and Technologies: Updates for 2022

It’s amazing how Java remains among the top development languages and platforms for so long, and by now it’s probably older than some of the developers that are using it.  
In 2021 it’s still in the top 5 according to the StackOverflow Developer Survey 


All thanks to the Java technologies innovation. The platform is evolving to meet the needs of the community and the global industry trends. Java keeps up with the serverless architecture, data science, IoT and reactive programming. 

The Symphony Solutions Java team has analyzed and presented their selection of the latest Java technologies and worldwide software development trends that influence the platform. Let’s continue to inspect what is sure to hit the spot, what remains relevant and what are some of the entirely new predictions. 

Machine Learning with Eclipse Deeplearning4j 

Eclipse Deeplearning4j is gaining popularity in Java nowadays. It is a library for machine learning written in Java for use in the JVM environment with its first preview released in March 2020. 

Developed specifically to be used in the JVM environment, it is compatible with other JVM languages. Deeplearning4j is considered a high-level framework that is used for building neural networks. This means that the toolset empowers you to perform a wide range of tasks that have to do with clustering and classifying data, as well as data analysis for high level predictions (e.g., weather forecast, predictions for the stock market, etc.). 

Deeplearning4j is used in cybersecurity for detecting fraud or anomalies, which makes it invaluable for use in fintech, e-commerce, and other sectors that require enhanced security for sensitive data protection. It can be integrated with other ML platforms (RapidMiner, Weka, Some interesting use cases include retraining and deploying models in JVM microservice environments, mobile devices, IoT, etc. 

New features in Java 14 and 15 

Java versions 14 and 15 have introduced new features that make for a more streamlined and clean code, making the life of Java developers worldwide easier, allowing them to focus on creating the most value without getting lost between lines of code or drowning in neverending documentation. 

Some of the new features that were introduced and should be on your checklist are the following: 

  • Record is a new type of class introduced in Java 15 to reduce boilerplate code and make it easier to create immutable data objects. 
  • Switch expressions have been established as a standard feature since Java 14, and are now able to return value and assign it to the corresponding variable.  
  • NullPointerException is another Java 14 feature, which is a step-up in debugging, as it points out the null variable and the name of the call that threw the exception.  
  • Hidden classes, introduced in Java 15, are a useful feature for developers who work with dynamic bytecode or JVM languages. 

In fact, any regular Java programmer could probably tell you about their pick-of-the-crop new features introduced in Java releases 12 through 17, as there surely is something to pick from with Oracle rolling out a new LTS release every two years, next to the quarterly updates for the previously introduced versions. 
Though the most used is still Java 8 version, the latest versions are starting to gain momentum in 2021. 

popular java versions in 2021

Java Concurrency 

Java concurrency is another popular technology in Java. Concurrency programming, means that multiple programs or applications can run simultaneously, which is supported through multithreading and synchronization. It’s a lightweight process that allows accessing data from different threads, that in Java constitute the path that is followed whenever a program is being executed. 

Threads are created by the Java Virtual Machine when you run the program, which may work with multiple threads simultaneously to run a Java application. Concurrency varies depending on other processes that run in the operating system – the number of threads that can run concurrently on a normal CPU depends on the number of processors in the system, whereas a high-volume application can run thousands of threads with GPU without interruption. 

Java concurrency helps improve the throughput of the program and optimize the process, as you can run parts of the program in parallel and reduce the time that is required to complete a time-consuming task faster without reduced efficiency. 

What’s coming to replace Spring Boot

 Spring Boot is still the most trending Java-based framework that is used for creating microservices. It’s gained its popularity due to a gradual learning curve and simplicity of integration with other Java frameworks.  

popular framework

However, we are observing new frameworks rising to their popularity that may well become an alternative, that are more lightweight and perform on par or better than Spring Boot. 


Vert.x is another lightweight alternative to Spring Boot from Eclipse foundation. It is used for building reactive applications that are resilient and highly scalable. Vert.x is based on an asynchronous and non-blocking execution model. It also supports the use of multiple languages. When comparing Vert.x to Spring Boot in one of our latest articles, the former is vastly outperforming in terms of speed of processing concurrent requests, CPU and memory usage. 

Azure is the cloud competitor to AWS 

We can now observe steady growth in the popularity of Microsoft Azure as a competitor to AWS. What does it have to do with Java trends, you may ask? 

Java is the programming language of choice when it comes to cloud computing, due to the ease of use and it being possible to run the same program on different platforms. This makes selecting the right cloud environment oftentimes a big concern for Java developers who want to get the most out of the cloud services provided. For now, AWS is the cloud provider of choice for the majority, although Azure is catching up and generating a fanbase of its own. In fact, Microsoft Azure is working closely with the Java community on providing resources and tools to Java developers who want to work with cloud-native applications. 

Java developers may choose Azure as their prefered cloud computing platform for some or all of the following reasons: 

  • Windows integration. 
  • Built-in analytics tools. 
  • Strong PaaS solution. 
  • Highly visual and easy to use UI (little to no coding required). 
  • Reliable storage capabilities and secure data encryption. 
  • Active directory library for Java. 
  • Fully managed cloud infrastructure. 
  • Continuous integration and deployment tools. 

Whatever is your reason for opting for Microsoft Azure, the main point is that you meet your objective. And as practice shows, Azure has a growing popularity among startups and independent software vendors, and it’s used by more than 95% of Fortune 500 companies. 

Java Technologies and Trends In Retrospect: 2018-2019 

Java 10 and Java 11 

Our 2018 list of the latest Java technologies started with, well, Java. It was around that time when Java switched to releasing new versions every six months instead of three years. Fast releases mean more innovation. They also mean fewer differences between versions and a more complicated Long-Term Support (LTS). That’s why Oracle decided to provide LTS once every six releases or three years. Unfortunately, though, this only concerns the commercial support contract from Oracle. Public updates and other releases will only be updated for six months – until the next version comes out. 

Java 9 was the first incremental release, and two more came out in 2018: Java 10 and Java 11. Java 10, released in March 2018, introduced the local variable type inference and a new garbage collector interface. These features were supposed to simplify writing Java applications. But Java technologies innovation didn’t stop there. Java 10 has an improved JVM which is going to make it easier to use Docker containers. Java 11, released in September 2018, has all the features mentioned above plus it’s the first LTS support version since Java 8. The next LTS version will be released in September 2021. 

Keep Сalm and Learn Kotlin 

Kotlin has every chance to become a programming marvel. According to the Stack Overflow Survey 2018, Kotlin was the second most loved language among developers. In 2021 the interest to this language is still high – it’s in the top 15 on the list of the most loved languages among developers though the interest is a bit decreased. The Symphony Solutions Java team has already given their credit to this programming language. 

The language was designed to be loved by Java developers. It’s 100% interoperable with Java code, so much so that classes written in Kotlin can be mixed up with classes in Java and the solution will work seamlessly. Seriously, any Java library can be used within Kotlin. And since a lot of gigantic enterprise systems and Android applications use Java, a new and lightweight Kotlin is a gift to Java developers. 

While you may think it’s just another Java Virtual Machine language, Kotlin was designed by JetBrains, a company that knows a thing or two about the perfect Java IDE. Developed with the gaps of other JVM languages in mind, Kotlin is an expressive language (read: less error-prone) that’s not as verbose as Java. Its data classes and list operations reduce boilerplate code, and Kotlin offers nullability-safe extension functions and higher-order functions all Android developers will appreciate. 

Though Kotlin has some interesting use cases, it’s the Android apps niche that can and probably will propel it. It’s now the first-level language for Android app development. Google’s appreciation for the language and the commitment to support Kotlin means a lot for its future growth and popularity. It will be interesting to see if Kotlin finds its place in enterprise applications development or not. 

Reactive Java 

Reactive programming is nothing new, but it’s become more relevant than ever. The volumes of data are skyrocketing; the computational power is increasing. Users demand software integrity, fast updates, and non-stop synchronization. Processing numerous events becomes a pain in the back(end) for Android. It’s time to switch to a programming paradigm where you define the source of data and the consumer of that data. 

RxJava, first released in 2013, is still being quite actively used to this day. It is the reactive extension (API for implementing reactive programming) for the JVM. When you connect the consumer to the source of data, RxJava pushes the data to the consumer. This library can help developers build asynchronous, concurrent and resilient Java applications. It also makes the code look less bulky and more elegant. 

From Microservices to Serverless 

One of the most significant global trends in software design from 2018 up to these days is the shift from microservices to serverless architecture, and the current Java technologies also couldn’t resist it. Let us refresh your memory. The microservices architecture means that the system is modular and all of its components can be changed or replaced independently without harming the system. Microservices remain a popular way of building complex systems that comprise independent components, and Java developers find their ways around overcoming any shortcomings microservices may present to get the most out of the microservice architecture in Java. Since serverless is still at times a luxury solution with the cost of development and maintenance, we are not taking microservices off the shelves just yet. 

The serverless architecture means that you can build and deploy the code without having to configure the underlying servers. But the best part about serverless computing is that it breaks modules down into parts smaller than microservices. This allows almost infinite scaling. Also, that level of modularity gives developers a chance to visualize complex processes going on in their software, so it’s much easier to improve performance, reduce bottlenecks and even make architectural decisions. To sum up, the serverless approach gives you granular control over the architecture of a solution and simple horizontal scalability. 

So, how do you go serverless with Java? Two words: AWS Lambda, a serverless computing platform. All you have to do is create an AWS Lambda Function and implement a predefined interface. 

AWS Serverless Java Container 

The Java wrapper known as aws-serverless-java-container  (version 1.7) makes working with AWS Lambda easier. A Serverless Java Container natively supports API Gateway proxy integration for Lambda with request and response mappings. You can also create custom model mappings using VTL. The AWS Gateway API starts each Lambda as a container and then translates API Gateway proxy events into the request format that’s accepted by the Lambda. 

However, containers have the limitations of a single request at a time. Secondly, the bulkier the application, the higher the latency. To avoid this, the code footprint should be as small as possible with a minimum of required dependencies. 

If you want something smarter, though, look up Service Bloks. They are cloud-native apps that combine the advantages of microservices with the scalability of serverless functions. A basic service block consists of a Service Core and Functions. A service core is a Spring Boot application, and it’s responsible for communication and dispatching events to serverless functions inside a block. 

Data Science with Java

You can use Java pretty much anywhere, and data processing is no exception. The fact that Java is a high-performance, general-purpose, compiled language just proves the point. No matter what popular framework you choose, Hadoop or Apache Spark, there’s a well-supported Java client or implementation to work with. Not to mention clients for all sorts of SQL and NoSQL databases. 

Thanks to a big community, there are many libraries for data processing and cloud computing as well as machine learning. Keeping your ETL production code, data processing, and machine learning in the same ecosystem is obviously a good idea. 

Of course, Java is not perfect. Because it is a wordy programming language, Java isn’t the best fit for R&D or statistical applications. That’s why data scientists choose dynamically typed languages like R and Python instead. Competing with R is especially hard since it was created for statistics and research. Despite that, Java is successfully being used in Data Science thanks to its ubiquity, performance and seamless integration of the data science code into an existing solution. 

Java Maximizes Its Effects on Scripting Languages 

Not every programmer is a pro in Java development, but Java’s effects on other languages are something many of them experience. Just think of the massive number of languages that are now executed on the Java Virtual Machine. Various widely-appreciated scripting languages were written using Java, created for or ported to the JVM. This allows them to make use of the rich Java ecosystem. 

Java developers sometimes choose scripting languages as a quick and easy solution for tasks like prototyping, algorithms and mathematics. They are especially helpful when you need to perform a complex task in a minimal number of steps. 

Think of Groovy, JRuby and Jython. These popular and tightly Java-integrated scripting languages can help developers incorporate scripts originally written in Ruby or Python with Java libraries. You can get extra info and some JRuby inspiration by reading success stories on GitHub

Java has also become one step closer to scripting languages with the introduction of Java Specification Request (JSR) 223. Along with Java SE 6, which includes built-in support for script engines, it provides a standard interface and API to interact with dynamic languages running on the Java platform. 

Java Development Propels IoT to the Productive Future 

Another niche where Java leads the pack is IoT architecture environment. According to the IoT Developer Survey by the Eclipse Foundation, Java is the favorite language for building IoT solutions. And the future Java trends predict the same, due to its interoperability and portability. All thanks to JVM, as it lets developers write code locally and then move it to small pieces of hardware like chips. Java is one of the best choices for cloud and gateway development from the entire IoT infrastructure. Isn’t it convenient to use the same ecosystem for data measurement, collection and analysis? 

At the beginning of 2019, Oracle also updated the Java Card platform which provides security for smart cards and other limited-memory device applications. Version 3.1 of the platform offers increased support for IoT devices. 

Summing Up 

There are numerous reasons why Java keeps landing among the top technologies for business and web. It’s the combination of simplicity and robustness, the popularity of Android and web applications, and, of course, an enormous, friendly community. 10 million developers can’t be wrong. 

Although no fundamentally new Java technologies are going to be delivered anytime soon, the platform is flourishing and has no intention to stop. The latest Java technologies follow global trends in software design and development. This includes reactive development, serverless architecture, and data science. The rise of the JVM languages, the breakthrough of Kotlin, and the perfect match of Java and IoT infrastructure prove that Java has no intention of stopping in future. 

You may have noticed that some of the Java trends overlap with the previous years’ tendencies. That’s no surprise since the Java platform manages to balance beautifully between stability and innovation, and continues its influence on the rest of the programming world. 

At Symphony Solutions, we care about Java and are always eager to discuss modern Java technology. Check our open Java job positions and do not hesitate to apply! 

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