Industrial Data Management | Velotic
Chat with us

Industrial Data Management software

Connect, collect, store, contextualize, and use industrial data with software that helps organizations create a trusted data foundation for operational visibility, analytics, AI, and enterprise decision-making.

Placeholder image Talk to an expert
Overview

Turn industrial data into operational value

Subscribe to Velotic’s LinkedIn newsletter for practical insights on connecting, managing, contextualizing, and using industrial data to drive better decisions.

Subscribe
Capabilities

Industrial Data Management capabilities

From device connectivity and time-series storage to asset modeling, contextualization, and application enablement, Velotic provides the capabilities organizations need to make industrial data reliable, accessible, understandable, and useful.

Industrial connectivity & acquisition

Connect PLCs, machines, sensors, controllers, and other industrial systems across vendors and protocols. Collect and normalize their data to create consistent, application-ready information for OT and IT systems.

Technician working with connected equipment

Time-series collection & storage

Capture high-volume process values, equipment data, alarms, and events at industrial speed. Compress and securely retain that data for fast retrieval, reporting, compliance, long-term analysis, and optimization.

Technician working with connected equipment

Data reliability and availability

Protect the continuity and integrity of industrial data through buffering, store-and-forward collection, redundancy, failover, and highly available architectures.

Technician working with connected equipment

Industrial data contextualization

Organize data around assets, equipment, relationships, and operational structures so applications and users can interpret what raw industrial values represent.

Technician working with connected equipment

Industrial data integration

Deliver real-time and historical data to MES, HMI/SCADA, analytics, cloud platforms, data lakes, enterprise systems, and other applications through open interfaces.

Technician working with connected equipment

Industrial application enablement

Use connected and contextualized industrial data to build applications for monitoring, performance management, connected work, analytics, and other operational use cases.

Technician working with connected equipment

Is your industrial data ready for AI?

Industrial AI depends on more than access to large volumes of data. Learn how connectivity, data quality, context, governance, and scalable industrial data architecture can help transform fragmented OT information into a trusted foundation for analytics and AI.

Watch the webinar
Velotic Portfolio

The power of the portfolio

Three products, one connected foundation. Each plays a distinct role in your Industrial IIoT architecture — and together, they cover every layer of your operation.
Kepware®

Securely connects machines, devices, and control systems to modern applications through universal industrial protocol support.

  • 150+ industrial protocols
  • OPC UA & MQTT support
  • Legacy device connectivity
  • Secure data bridging
  • Real-time data flow

Explore Kepware

Proficy®

Helps industrial teams see, understand, and optimize their operations through HMI/SCADA, MES, and data historian capabilities.

  • HMI/SCADA visualization
  • Smart Factory MES
  • Industrial data historian
  • Operations Hub
  • Industrial Analytics

Explore Proficy

ThingWorx®

Transforms data into insight, applications, and outcomes through an enterprise IIoT platform built for industrial scale.

  • IIoT application development
  • Digital twin orchestration
  • Predictive analytics
  • Remote operations
  • Enterprise integration

Explore ThingWorx

See how our products work together

Velotic connects industrial assets, preserves operational history, and adds asset and relationship context to industrial data. Together, Kepware, Proficy Historian, and ThingWorx create a scalable data foundation that spans equipment, plant systems, connected applications, and the enterprise.
Velotic product bundles

Kepware + Proficy Historian

Kepware connects PLCs, machines, sensors, and industrial systems and standardizes the data they produce. Proficy Historian collects and securely stores that data at high speed so it remains available for monitoring, reporting, analysis, and long-term operational use.

Together, they help organizations:

- Connect legacy and modern industrial equipment - Standardize access across diverse vendors and protocols - Collect high-frequency equipment and process data - Preserve real-time data, alarms, and events over time - Reduce data loss through reliable collection architectures - Supply trusted historical data to industrial and enterprise applications

Learn more

Kepware + ThingWorx

Kepware provides reliable access to real-time data from industrial equipment. ThingWorx models the connected assets and their relationships, adds operational context, and makes the resulting information available to applications and workflows.

Together, they help organizations:

- Connect equipment across different vendors and protocols - Normalize device data for consistent application access - Model machines, lines, sites, and asset relationships - Combine real-time equipment data with business context - Build connected monitoring and operational applications - Extend industrial information to additional users and use cases

Learn more

Proficy Historian + ThingWorx

Proficy Historian provides a secure, scalable record of real-time and historical industrial data. ThingWorx adds asset models and relationship context that help applications and users interpret that information within the structure of their operations.

Together, they help organizations:

- Connect historical trends with asset and site structures - Make time-series data easier for applications to interpret - Compare equipment and operating performance over time - Support monitoring, investigation, and performance analysis - Extend trusted industrial history into connected applications - Prepare contextualized operational data for analytics and AI

Learn more

Kepware + Proficy Historian + ThingWorx

Kepware provides the connectivity foundation, Proficy Historian creates a trusted record of industrial time-series data, and ThingWorx adds asset context and application enablement. Together, they create an end-to-end industrial data architecture from the edge to the enterprise.

Together, they help organizations:

- Connect industrial assets and systems at scale - Standardize and aggregate real-time OT data - Reliably collect and retain operational history - Organize information around assets and relationships - Make data available to industrial and enterprise applications - Create a scalable foundation for visualization, analytics, optimization, and AI

Learn more
Case Studies

Case studies

View all
Resources

Resources

View all

All Resources

Blog

Video

Brochure

Buyer's guide

Data sheet

E-book

Industry analyst report

Infographic

Report

Webinar

White paper
Frequently Asked Questions

Frequently asked questions

What is industrial data management?

Industrial data management is the process of connecting, collecting, storing, organizing, contextualizing, securing, and distributing data generated by industrial equipment and operations. It encompasses information from PLCs, machines, sensors, control systems, historians, MES, maintenance systems, and other OT and IT sources.

Industrial data management helps organizations create reliable access to real-time and historical information. It ensures that operational data can be understood and used by people, industrial applications, analytics platforms, enterprise systems, and AI tools.

What is industrial data management software?

Industrial data management software is a collection of technologies used to acquire, standardize, store, contextualize, and distribute industrial data. It can include industrial connectivity platforms, data historians, edge technologies, asset models, integration services, and industrial application platforms.

Velotic industrial data management solutions include Kepware for connectivity and data acquisition, Proficy Historian for high-speed time-series collection and storage, and ThingWorx for asset modeling, contextualization, and application enablement.

What challenges does industrial data management address?

Industrial data is often fragmented across equipment, proprietary protocols, plants, historians, databases, and applications. Organizations may struggle with inconsistent naming, inaccessible legacy equipment, missing context, unreliable collection, duplicated integrations, and different data models across sites.

Industrial data management addresses these challenges by establishing consistent connectivity, reliable historical storage, shared asset context, and governed access to operational information. This helps reduce data silos and makes industrial data easier to find, understand, trust, and use.

What types of industrial data need to be managed?

Industrial organizations manage many types of data, including equipment states, sensor readings, process values, setpoints, cycle counts, temperatures, pressures, speeds, energy consumption, alarms, events, quality measurements, production counts, and maintenance indicators.

This information can arrive continuously and at high frequency from thousands or millions of data points. Industrial data management systems must therefore support rapid ingestion, efficient storage, reliable access, operational context, and long-term retention.

What is an industrial data historian?

An industrial data historian is specialized software designed to collect and store high-frequency time-series data from industrial operations. Unlike a conventional relational database, a historian is optimized for continuous data ingestion, compression, rapid time-based retrieval, and long-term retention.

Proficy Historian collects industrial time-series, alarm, and event data at high speed and stores it efficiently on-premises or in the cloud. That information can then be retrieved for visualization, troubleshooting, reporting, compliance, analytics, and optimization.

How is a data historian different from a traditional database?

A traditional database is generally designed for transactional or business records organized into structured tables. A historian is optimized for continuously changing values that are timestamped and generated at industrial speed by equipment, sensors, and control systems.

Historians use specialized compression, indexing, collection, and retrieval techniques to manage large volumes of time-series data efficiently. They also commonly provide industrial features such as collectors, buffering, store-and-forward capabilities, tag management, alarm and event storage, and integration with operational systems.

What is industrial connectivity software?

Industrial connectivity software links PLCs, controllers, machines, sensors, and industrial systems with the applications that need their data. It communicates using industrial protocols and converts device-specific information into formats that other OT and IT systems can consume.

Kepware provides a common connectivity layer for diverse industrial assets. It helps organizations avoid building and maintaining separate point-to-point connections for every combination of device, protocol, and consuming application.

What is industrial data contextualization?

Industrial data contextualization adds meaning and relationships to raw operational values. A tag such as a temperature or motor speed becomes more useful when it is associated with a specific machine, production line, site, process, product, operating state, or maintenance condition.

ThingWorx can model industrial assets and relationships and combine equipment data with information from other systems. This creates context that helps applications and users understand what the data represents and how different operational elements relate to one another.

How do Kepware and Proficy Historian work together?

Kepware connects to industrial equipment and standardizes access to the real-time data it produces. Proficy Historian collects and stores that information as a reliable time-series record.

Together, the solutions create a path from machines and control systems to secure historical storage. This allows organizations to connect diverse assets, capture operational history, investigate events, analyze trends, and make equipment data available to other industrial and enterprise systems.

How do Kepware and ThingWorx work together?

Kepware connects industrial equipment and supplies standardized real-time data. ThingWorx models the connected assets, adds relationships and business context, and uses the data within industrial applications.

This combination helps organizations bridge the physical and digital layers of their operations. Equipment values can be associated with machines, production lines, facilities, and operational use cases rather than remaining isolated device tags.

How do Proficy Historian and ThingWorx work together?

Proficy Historian maintains a reliable record of industrial time-series data, while ThingWorx organizes information around assets and application use cases. Connected applications can use current and historical data to monitor performance, investigate conditions, and understand how assets behave over time.

The combination helps make historical operational data more accessible and meaningful within asset-centric applications, analytics, workflows, and enterprise use cases.

Can industrial data management software connect legacy equipment?

Yes. Industrial connectivity software can connect many legacy PLCs, controllers, machines, and proprietary systems alongside newer equipment. Kepware supports a broad range of industrial drivers and protocols, allowing organizations to access data from heterogeneous environments without replacing functioning equipment solely to modernize connectivity.

This can help manufacturers and other industrial organizations extend the value of existing assets while creating a more standardized data architecture for future applications.

Can industrial data be managed in the cloud?

Yes. Industrial data can be managed through on-premises, cloud, or hybrid architectures. Cloud-based industrial data management can support centralized access, enterprise-scale aggregation, elastic storage and processing, managed infrastructure, and integration with cloud analytics and data platforms.

Hybrid architectures allow organizations to keep time-sensitive collection and operational functions close to production while securely extending selected data to cloud applications. The right architecture depends on latency, reliability, security, regulatory, sovereignty, and business requirements.

How does industrial data management support analytics and AI?

Analytics and AI depend on data that is available, accurate, consistent, sufficiently historical, and connected to meaningful operational context. Missing data, inconsistent tags, isolated systems, and poorly understood relationships can limit model accuracy and the usefulness of analytical results.

Industrial data management creates the foundation by connecting source systems, preserving high-quality operational history, and organizing information around assets and processes. This makes it easier to prepare industrial data for descriptive, diagnostic, predictive, prescriptive, and generative AI use cases.

How does industrial data management support IT/OT convergence?

Industrial data management provides controlled ways for OT systems to share operational information with IT applications and cloud platforms. Connectivity, historians, open interfaces, asset models, and contextualization help translate equipment-level data into information that enterprise systems can consume.

This allows IT and OT teams to collaborate around a common data architecture while respecting the performance, reliability, security, and governance requirements of industrial operations.

How do organizations choose industrial data management software?

Organizations should evaluate the diversity of their equipment and protocols, required collection speeds, data volumes, retention periods, reliability needs, deployment preferences, security requirements, and intended data consumers. They should also consider interoperability, contextualization, administrative effort, scalability, and support for open interfaces.

The right architecture should address immediate connectivity and storage needs while providing a scalable path for multisite visibility, connected applications, analytics, enterprise integration, and AI.

Which industries use industrial data management software?

Industrial data management software is used across manufacturing, utilities, energy, pharmaceuticals, food and beverage, chemicals, metals and mining, water and wastewater, oil and gas, automotive, aerospace, and other asset-intensive industries.

Although their processes differ, these industries all generate large volumes of operational data and depend on reliable access to that information for visibility, troubleshooting, compliance, optimization, and decision-making.