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Solution

Event-driven architecture for real-time industrial IoT data streaming

Build a responsive data architecture that’s ready for AI/ML, automation, and scale.

Scalable industrial use cases powered by EDA and MQTT

AI-ready operations

Trigger real-time workflows and stream data into AI and ML systems to enable smarter, faster, and more autonomous operations.

IT/OT convergence

Break down silos by syncing systems, from edge to cloud across the enterprise, through a common event layer.

Asset tracking & remote monitoring

Use event updates to monitor the location and health of assets in real time.

Real-time predictive maintenance

React instantly to anomalies and avoid costly failures with event-based alerting.

Continuous OEE monitoring

Track metrics such as Overall Equipment Effectiveness (OEE) as events happen.

Safety and compliance alerts

Get instant visibility and response for safety-critical events or regulatory thresholds.

Why HiveMQ is the backbone of event-driven industrial architectures

MQTT for scalable events

Capture millions of industrial events per second from edge devices with HiveMQ’s reliable, low-latency MQTT architecture, purpose-built for large-scale IIoT environments.

Edge-to-cloud architecture

Seamlessly stream events from SCADA, MES, and OT systems to platforms like Kafka, Snowflake, and cloud-based AI engines, creating a single, responsive data pipeline.

Built for industrial DataOps

Enable rapid development, observability, and deployment of event-driven applications, bringing DevOps agility to industrial environments without compromising reliability.

Unified Namespace for shared context between OT and IT

Organize events into standardized topic hierarchies so every system from OT to IT can access real-time data with clear context and meaning.

AI-ready data governance & standardization

Ensure consistency, context, and compliance across all your event streams, thus fueling analytics, AI/ML, and automation with trusted, contextualized inputs.

Flexible, future-proof deployment

Deploy HiveMQ in the cloud, on-premise, or hybrid setups with robust extension support for integrating legacy systems, enterprise platforms, and evolving IIoT needs.

Resources

IIoTIoT Data StreamingMQTT

Solving Common Industrial IoT Data Streaming Challenges with MQTT

Struggling with real-time IIoT data flow? Learn how MQTT solves legacy integration, scaling, reliability, and security challenges in manufacturing.

Blog
AIIoT Data StreamingMachine LearningSmart Manufacturing

Industrial IoT Data Streaming for Continuous Intelligence Through AI/ML

Industrial IoT data streaming unlocks continuous intelligence with AI/ML, driving smarter decisions, better performance, and real-time insights.

Blog
IIoTIoT Data StreamingSmart Manufacturing

The Business Impact of Real-Time Dashboards and Industrial IoT Data Streaming Analytics

Discover how real-time dashboards and industrial IoT data streaming enable instant insights, faster decisions, and smarter operations across manufacturing.

Blog

FAQs

Yes. MQTT’s pub/sub model is tailor-made for real-time, event-driven architectures.

Yes. HiveMQ acts as the bridge, ingesting events with MQTT and stream them to Kafka for processing.

You get localized responsiveness at the edge, combined with centralized analytics in the cloud.

Yes. Streaming provides the real-time backbone that EDA relies on.

Yes, EDA enables instant responses to anomaly events, reducing unplanned downtime.

UNS provides a structured topic hierarchy that ensures all systems interpret event data in a consistent, meaningful way.

Yes. HiveMQ is built for enterprise-scale deployments with clustering, high availability, and support for millions of concurrent connections, making it ideal for multi-site industrial EDA strategies.

HiveMQ’s extension SDK framework enables seamless integration with SCADA, MES, and other legacy systems, bridging old protocols with modern event-driven architectures without major overhauls.

HiveMQ standardizes and structures event data using MQTT and Unified Namespace, ensuring clean, contextual, and consistent data flows that feed AI/ML models with minimal preprocessing.

HiveMQ is designed for fast, low-friction deployment. With flexible integrations, extension SDKs, and flexible deployment options, most customers achieve value in weeks, not months or years.

Get started with HiveMQ today

Choose between a fully-managed cloud or self-managed platform. Our experts can help you with your solution and demonstrate HiveMQ in action.