An old airport customer of mine (whilst I worked for another company) used to pop someone next to a busy runway with a stopwatch strapped round their neck. The unfortunate person had to manually log the time aircrafts spent on the runway to measure the runway occupancy. All very archaic. Even in those days.

We’re continuously releasing new capabilities to enable more people to be productive and compliant when working with Apache Kafka. Our engineers have been hard at work on a great Christmas present for our amazing community of Kafka users. Before unwrapping our latest and greatest release, here’s a sneak peak of what’s inside.

In this article we are going to explore lateral joins. "What is a lateral join?" you may ask. It's a new kind of join that allows to extract and work with the single elements found inside an array, as if the array was a normal table. Lenses 4.1 comes with a lot of new features that make your life easier when working with arrays: we introduced 6 new functions to work with arrays, better support for array literals, and lateral joins.

If you’re moving data in and out of Kafka, chances are you’re using Apache Kafka Connect. The strength of the Kafka community means we have a large catalog of available connectors for hundreds of different technologies, helping to accelerate the integration of Kafka with 3rd party systems.

Several years ago when I was working on a big data project, I saw something a data engineer shouldn’t see. Curious to understand the level of detail in a new credit score dataset we’d received in our data lake, I queried it. I was surprised at how easily and suddenly my screen was flooded with the mortgage history, overdraft limits and year-end financial statements of my colleagues, and I felt deeply uneasy.