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HiveMQ Pulse

Next-generation Distributed Data Intelligence Platform

HiveMQ Pulse creates a governed foundation for operational data - delivering structure, consistency, and insight across the enterprise where decisions are made.

The Business Impact of Trusted Data

$0M

Poor data quality costs organizations millions each year, increasing complexity and hindering decisions (Gartner)

0% Higher Revenue

Companies successfully operating in real-time environments outperform competitors (MIT)

0% Faster Decisions

Organizations utilizing live data insights improve their decision-making speed (Deloitte)

Why Real-time Distributed Data Intelligence?

Organizations are generating more operational data than ever, but to drive real business impact, they need to extract value quickly and make that data AI-ready.

Why Real-time: Decisions need to happen the moment events occur, not hours or days later. Delayed insights are missed opportunities.

Why Distributed: We live in a distributed world, data is created everywhere, from edge devices to factories to cloud systems. Instead of moving everything to a centralized cloud, extract insights where the data lives.

Why Intelligence: Raw data isn’t enough. You need intelligence layered on top to deliver operational insights that inform action, unlock efficiency, and enable better business outcomes.

HiveMQ Pulse Key Benefits

HiveMQ Pulse is a real-time distributed data intelligence platform that turns fragmented, inconsistent operational data into structured, insight-rich streams for real-time decisions, analytics, and AI.

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Unified Data Management Feature of HiveMQ Pulse Distributed Data Intelligence Platform

Unified Data Management

Ensure data consistency by modeling, enriching, and governing information in a Unified Namespace - enabling interoperability, standardization, and seamless OT–IT integration.

Real-Time Actionable Insights Feature of HiveMQ Pulse Distributed Data Intelligence Platform

Real-time Actionable Insights

Transform and validate data as it flows - reducing delays, improving efficiency, and giving teams immediate access to trusted information where it matters most.

Distributed Intelligence Feature of HiveMQ Pulse Distributed Data Intelligence Platform

Distributed Intelligence

Pulse processes and validates data at the edge, reducing latency and enabling faster, more reliable insights across edge, site, and cloud.

AI Feature of HiveMQ Pulse Distributed Data Intelligence Platform

AI and Analytics Readiness

Deliver clean, governed operational data from edge to cloud — establishing a trusted foundation for analytics today and AI initiatives tomorrow.

As UNS evolves it will drive deeper integration, smarter operations,and significant innovation across industrial ecosystems.

Anand Taparia

/

Principal Analyst, IoT Analytics

HiveMQ Pulse Technical Architecture

With a flexible architecture uniquely suited to support a Unified Namespace (UNS) approach, HiveMQ Pulse allows you to build, govern, and derive insights from distributed devices and systems, providing a single, structured view of operational data across the enterprise.

HiveMQ Pulse Architecture
pulse-server

Pulse Server

Manages information models, authorizes agents, and coordinates configuration across environments.

Pulse-Agent

Pulse Agents

Perform in-stream transformation and validation close to where data is created.

Pulse-Client

Pulse Client

Provides secure connectivity and management between operational systems and Pulse Server.

HiveMQ Pulse Insights Graphs

HiveMQ Pulse Key Technical Capabilities

Unified Namespace Creation & Governance: Define and govern a Unified Namespace that ensures data consistency across brokers, agents, and sites. Eliminate manual tag management and site-specific variations with reusable, governed models that align OT and IT.

In-Stream Transformation & Enrichment: Transform, clean, and enrich data as it flows — right where it’s created. Reduce fragile scripts and preprocessing by applying business logic directly at the edge.

Agent-Based Execution & Validation: Pulse Agents validate, enforce, and execute close to the data source. Catch errors early, apply governance locally, and preserve context before data moves downstream.

Edge-to-Cloud Data Governance: Apply consistent models and governance from edge to cloud through Pulse Server. Enable repeatable rollouts and reduce drift across environments.

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