Another year, another Christmas break, another OSBDET release! It’s remarkable how quickly time flies… yet here we are again, and I couldn’t be more excited to share what’s new.

I have to admit, this has officially become my favorite holiday tradition. There’s something incredibly satisfying about dedicating time to building and refining tools that will benefit students throughout the year, all while enjoying the company of family and friends. It’s the perfect balance of creative work and relaxation.

So, without further ado, OSBDET 2026 Release 1 is officially ready for the upcoming intakes! The development process continues to get smoother with each iteration, which means I can invest more energy into what really matters: fine-tuning the learning experience and integrating emerging technologies that will help students understand the big data landscape.

If you’re new here, let me give you a quick overview of what OSBDET is all about:

OSBDET is a collection of automated scripts that download and configure open-source Big Data frameworks and tools on a single machine. The primary goal? To create a fully functional course environment (as a virtual machine) in just minutes. This project was born out of necessity after spending countless days manually building a course environment years ago (detailed in my post ‘Building an analytics and multi data-set OVA for learners‘), I realized there had to be a better way. My students come from diverse backgrounds, and while some are very comfortable with technology, others are not. That’s why OSBDET focuses on simplified, accessible versions of the same technologies used in commercial big data products, making them easier to study and understand.

The scripts themselves are available in the OSBDET Github repository and are designed for those who want full control over their environment setup. However, I’ve also created something more accessible: two ready-to-use Debian GNU/Linux virtual machines that come pre-loaded with all the technologies needed for my courses:

• OSBDET’26r1.utm.zip (10.72GB) – A UTM-compatible virtual machine optimized for Apple Silicon (arm64) processors. This has been tested on macOS Tahoe running on an M3-based Mac with UTM v4.7.4.
• OSBDET’26r1(amd64).ova (9.64GB) – A VirtualBox-compatible virtual machine for Intel (amd64) processors, suitable for Windows and macOS systems. Tested on Windows 11 and macOS Monterey (Intel-based Mac) with VirtualBox 7.2.4.

The web interface introduced in earlier releases continues to be a game-changer. By consolidating access to all frameworks in one place, it dramatically reduces the overhead of managing multiple tools during lab sessions. This means students can focus on understanding big data concepts and building pipelines rather than wrestling with configuration files. You can access the interface by pointing your browser to http://localhost:2026.

What’s New in This Release?

This year’s release brings several exciting updates:

All core frameworks have been upgraded to their latest stable versions, carefully selected to ensure they work seamlessly with the course materials. You’ll find JupyterLab 4.4.9, Apache NiFi 2.7.2, Apache Hadoop 3.4.2, Apache Spark 3.5.7, Apache Kafka 4.4.1, MariaDB 11.8.3, Apache Superset 5.0.0, MongoDB 8.0.17 CE, MinIO (December 2024 release), Kestra 1.1.11, Grafana 12.3.1, and OpenMetadata 1.11.0.

The headline addition this year is ClickHouse 25.12, a powerful columnar database designed for real-time analytical workloads. I’ve been wanting to include an OLAP-focused solution in the environment for a while now, and ClickHouse fits the bill perfectly. It opens up new possibilities for exploring real-time analytics and understanding how columnar storage differs from traditional row-based systems… concepts that are increasingly important in the big data world.

Keeping the Momentum Going

What keeps me motivated to continue evolving OSBDET year after year? Simple: the feedback. Hearing from students that this environment helped them grasp complex big data concepts, or learning that fellow professors have adopted it for their own courses… that’s incredibly rewarding. Knowing that this personal project has a tangible impact on how people learn about big data technologies makes every hour spent during the holidays absolutely worthwhile.

This is more than just a course environment; it’s a labor of love that bridges the gap between theory and practice, making big data accessible to anyone willing to learn.

As always, I’ve prepared a video walkthrough to help you get started with OSBDET 2026 Release 1. Whether you’re a student preparing for upcoming courses or an educator looking to explore the environment, the video will guide you through installation and initial setup:

Here’s to another year of learning, building, and exploring the fascinating world of big data technologies!

Raúl