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Learn how to produce and consume records with Apache Kafka Java client library.

Table of Contents When an application written for the Java Virtual Machine is running, it constantly creates new objects and puts them on the heap. Well, at least in the vast majority of the cases. Such objects can have a longer or shorter life, but at some point, they stopped being referenced from the code. Unlike languages like C/C++, we don’t have exact control over when the memory will be freed – freeing the memory is the garbage collector’s job.

The Java Management Extensions (JMX) framework is a Java technology that includes tools for managing and monitoring applications, system objects, and service-oriented networks. The JMX framework is designed to simplify the management of local and remote Java applications. The JMX framework introduces the concept of MBeans for real-time management of applications, whereby resources are represented by objects called MBeans (Managed Beans).

As two of the most popular and practical languages out there, should you choose Java or Python for your next project? Is one of these languages a clear-cut better option? The answer is a long one. According to GitHub’s annual Octoverse report, Python has now climbed to the second most popular language in usage, pushing Java down to third place.

In 2023, Java is still the third most popular programming language in the world. It encompasses a vast ecosystem and more than 9 million Java developers worldwide. Java’s popularity comes down to a few key advantages; it’s a platform-independent language (write once, run anywhere) that follows the object-oriented programming paradigm and is straightforward to understand, write, and debug.

Although Java has been around for 27 years, enterprise applications still favor it as one of their preferred platforms. Java's functionality and programming flexibility increased concurrently with technological advancement, keeping it a useful language for more than 25 years. Outstanding examples of this progression include new garbage collection algorithms and memory management systems.

With billions of devices and applications producing time series data every nanosecond, InfluxDB is the leading way to store and analyze this data. With the enormous variety of data sources, InfluxDB provides multiple ways for users to get data into InfluxDB. One of the most common data formats of this data is CSV, comma-separated values. This blog post demonstrates how to take CSV data, translate it into line protocol, and send it to InfluxDB using the InfluxDB CLI and InfluxDB Client libraries.