Articles tagged as time series database

10 Predictive Maintenance Platforms for Manufacturing 2026: Featured at IIoT World Days 2025
· Predictive Maintenance

10 Predictive Maintenance Platforms for Manufacturing 2026: Featured at IIoT World Days 2025

As manufacturing moves toward 2026, the landscape of predictive maintenance is shifting from simple condition monitoring to “Agentic AI”, systems that don’t just alert you, but autonomously plan and execute multi-step resolutions. This evolution requires a robust data backbone to succeed.The following 10 platforms, highlighted in IIoT World Days 2025 panel discussions, represent the specialized […]

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Top 10 Energy Efficiency Solutions for Manufacturing 2026
· Energy

Top 10 Energy Efficiency Solutions for Manufacturing 2026

As manufacturers face volatile energy costs and aggressive decarbonization targets, the focus for 2026 is shifting from passive monitoring to active grid interaction. The following 10 platforms and technologies were highlighted by industry leaders during IIoT World Days 2025 as critical for optimizing energy consumption, stabilizing smart grids, and monetizing distributed assets. Toshiba (Virtual Power Plants) […]

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Beyond Dashboards: Manufacturers Want Predictive Data, Not Pretty Graphs
· Process Manufacturing

Beyond Dashboards: Manufacturers Want Predictive Data, Not Pretty Graphs

Walk into any modern factory and you’ll see walls of dashboards. Vibration graphs, torque curves, temperature plots, even “traffic-light” alarms glowing red or green. It looks sophisticated — until a critical press fails and the line stops anyway.That gap between visualizing and acting on data was the central theme of the panel “Predict, Prevent, Optimize: Real Results from Augmented Industrial […]

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Real-Time Data Plumbing: The Hidden Cost of Scaling Predictive Analytics
· Process Manufacturing

Real-Time Data Plumbing: The Hidden Cost of Scaling Predictive Analytics

When manufacturers discuss predictive analytics, the focus often jumps straight to machine learning models or AI. But as the panel “Predict, Prevent, Optimize: Real Results from Augmented Industrial Data”  made clear, the biggest challenge isn’t the math—it’s the plumbing. Data has to move quickly, cleanly, and at scale. Without that foundation, even the smartest model will […]

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Modernizing Without Disruption: A Practical Approach to Industrial Data Growth
· Digital Disruption

Modernizing Without Disruption: A Practical Approach to Industrial Data Growth

Industrial operations depend on data historians to record what’s happening on the line or in the field. But as systems evolve toward Industry 4.0, many teams find that their historians weren’t built for what’s next — the volume, velocity, and variety of time series data now generated by sensors, PLCs, and edge devices.Replacing these systems […]

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InfluxDB 3: Turning Industrial Data into Real-Time Action with Less Complexity
· Process Manufacturing

InfluxDB 3: Turning Industrial Data into Real-Time Action with Less Complexity

For manufacturers, utilities, and other industrial operators, time series data—information captured over time from machines, sensors, and control systems—is the backbone of modern operations. But as data volumes grow, many organizations are still struggling to keep up: storing the data is easy; using it effectively, in real time, is not.InfluxData’s release of InfluxDB 3 Core and […]

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InfluxData at Hannover Messe 2025: Making Industrial Data Work for You
· Predictive Maintenance

InfluxData at Hannover Messe 2025: Making Industrial Data Work for You

Hannover Messe 2025 is where manufacturers and industrial companies find practical solutions for real-world challenges. This year, InfluxData is bringing something different: an efficient, cost-effective way to handle industrial data in real time. Visit Hall 14, Booth H38, to see how InfluxDB simplifies data management, provides instant insights, and reduces storage costs.Why InfluxDB?Manufacturers deal with massive amounts of […]

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Data Retention for Long-Term IIoT Monitoring Using Time Series Databases
· Predictive Maintenance

Data Retention for Long-Term IIoT Monitoring Using Time Series Databases

Traditional industries have evolved by implementing many Industrial IoT practices, where we can get data from mechanical devices and sensors. Such real-time data monitoring helps perform better analysis, predict equipment failure, and reduce operating costs. However, IIoT creates enormous volumes of data that must be retained and controlled over long periods. Managing large volumes of […]

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Predictive Maintenance in IIoT: Leveraging Time Series Data for Equipment Longevity
· Connected Industry

Predictive Maintenance in IIoT: Leveraging Time Series Data for Equipment Longevity

The industrial Internet of Things (IIoT) helps bind machines, sensors, and systems together. They form a network of intelligent devices working together to generate and share data. This approach to managing devices has revolutionized how industries manage, monitor, and maintain their equipment. This connected network provides visibility into equipment performance, process throughput, and overall productivity. Predictive […]

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Augment/Replace OSI PI With a Time Series Database
· Connected Industry

Augment/Replace OSI PI With a Time Series Database

Industries are rapidly evolving from the era of computer automation (Industry 3.0) to a new phase—Industry 4.0. This shift introduces exciting technologies like the Internet of Things (IoT), artificial intelligence (AI), and big data analytics. These advancements allow businesses to collect and use real-time data, improving efficiency, productivity, and smarter decision-making.OSI PI is a crucial […]

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Augment/Replace Your SCADA System With a Time Series Database
· Connected Industry

Augment/Replace Your SCADA System With a Time Series Database

Industrial control systems are changing, and data is becoming increasingly important to contemporary operations. Supervisory Control and Data Acquisition (SCADA) systems have long served as the foundation of industrial control—even though they have their limitations. These challenges include limited data storage, difficulty scaling, insufficient capability for advanced real-time data analytics, and many more.These challenges faced […]

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