Industrial DataOps #12 with HiveMQ – Dominik Obermaier on MQTT, UNS and Massive Scale

Welcome to the final episode of our special Industrial DataOps podcast series. And what better way to close out the series than with Dominik Obermaier, CEO and co-founder of HiveMQ—one of the most recognized names when it comes to MQTT and Unified Namespace (UNS).

Dominik has been at the heart of the MQTT story from the very beginning—contributing to the specification, building the company from the ground up, and helping some of the world’s largest manufacturers, energy providers, and logistics companies reimagine how they move and use industrial data.

Every Company is Becoming an IoT Company

Dominik opened with a striking analogy:

"Just like every company became a computer company in the ‘80s and an internet company in the ‘90s, we believe every company is becoming an IoT company."

And that belief underpins HiveMQ’s mission—to build the digital backbone for the Internet of Things, connecting physical assets to digital applications across the enterprise.

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Today, HiveMQ is used by companies like BMW, Mercedes-Benz, and Lilly to enable real-time data exchange from edge to cloud, using open standards that ensure long-term flexibility and interoperability.

What is MQTT?

For those new to MQTT, Dominik explains what it is: a lightweight, open protocol built for real-time, scalable, and decoupled communication.

Originally developed in the late 1990s for oil pipeline monitoring, MQTT was designed to minimize bandwidth, maximize reliability, and function in unstable network conditions.

It uses a publish-subscribe pattern, allowing producers and consumers of data to remain decoupled and highly scalable—ideal for IoT and OT environments, where devices range from PLCs to cloud applications.

"HTTP works for the internet of humans. MQTT is the protocol for the internet of things."

The real breakthrough came when MQTT became an open standard. HiveMQ has been a champion of MQTT ever since—helping manufacturers escape vendor lock-in and build interoperable data ecosystems.

From Broker to Backbone: Mapping HiveMQ to the Capability Model

HiveMQ is often described as an MQTT broker, but as Dominik made clear, it's far more than that. Let’s map their offerings to our Industrial DataOps Capability Map:

Connectivity & Edge Ingest →

* HiveMQ Edge: A free, open-source gateway to connect to OPC UA, Modbus, BACnet, and more.

* Converts proprietary protocols into MQTT, making data accessible and reusable.

Data Transport & Integration →

* HiveMQ Broker: The core engine that enables highly reliable, real-time data movement across millions of devices.

* Scales from single factories to hundreds of millions of data tags.

Contextualization & Governance →

* HiveMQ Data Hub and Pulse: Tools for data quality, permissions, history, and contextual metadata.

* Pulse enables distributed intelligence and manages the Unified Namespace across global sites.

UNS Management & Visualization →

* HiveMQ Pulse is a true UNS solution that provides structure, data models, and insights without relying on centralized historians.

* Allows tracing of process changes, root cause analysis, and real-time decision support.

Building the Foundation for Real-Time Enterprise Data

Few topics have gained as much traction recently as UNS (Unified Namespace). But as Dominik points out, UNS is not a product—it’s a pattern. And not all implementations are created equal.

"Some people claim a data lake is a UNS. Others say it’s OPC UA. It’s not. UNS is about having a shared, real-time data structure that’s accessible across the enterprise."

HiveMQ Pulse provides a managed, governed, and contextualized UNS, allowing companies to:

* Map their assets and processes into a structured namespace.

* Apply insights and rules at the edge—without waiting for data to reach the cloud.

* Retain historical context while staying close to real-time operations.

"A good data model will solve problems before you even need AI. You don’t need fancy tech—you need structured data and the ability to ask the right questions."

Fix the Org Before the Tech

One of the most important takeaways from this conversation was organizational readiness. Dominik was clear:

"You can’t fix an organizational problem with technology."

Successful projects often depend on having:

* A digital transformation bridge team between IT and OT.

* Clear ownership and budget—often driven by a C-level mandate.

* A shared vocabulary, so teams can align on definitions, expectations, and outcomes.

To help customers succeed, HiveMQ provides onboarding programs, certifications, and educational content to establish this common language.

Use Case

One specific use case we’d like to highlight is that at Lilly, a Pharmaceutical company:

Getting Started with HiveMQ & UNS

Dominik shared practical advice for companies just starting out:

* Begin with open-source HiveMQ Edge and Cloud—no license or sales team required.

* Start small—connect one PLC, stream one tag, and build from there.

* Demonstrate value quickly—show how a single insight (like predicting downtime from a temperature drift) can justify further investment.

* Then scale—build a sustainable, standards-based data architecture with the support of experienced partners.

Final Thoughts: A Fitting End to the Series

This episode was the perfect way to end our Industrial DataOps podcast series—a conversation that connected the dots between open standards, scalable data architecture, organizational design, and future-ready analytics (and don’t worry, we have lots of other podcast ideas for the months to come :)).

HiveMQ’s journey—from a small startup to powering the largest industrial IoT deployments in the world—is proof that open, scalable, and reliable infrastructure will be the foundation for the next generation of digital manufacturing.

If you want to learn more about MQTT, UNS, or HiveMQ Pulse, check out the excellent content at www.hivemq.com or their article on DataOps.

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