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Industrial Data

Learn how to use CrateDB in industrial / IIoT / Industry 4.0 scenarios within engineering, manufacturing, and other operational domains.

In the realm of Industrial IoT, dealing with diverse data, ranging from slow-moving structured data, to high-frequency measurements, presents unique challenges.

The complexities of industrial big data are characterized by its high variety, unstructured features, different data sampling rates, and how these attributes influence data storage, retention, and integration.

Today’s warehouses are complex systems with a very high degree of automation. The key to the successful operation of these warehouses lies in having a holistic view on the entire system based on data from various components like sensors, PLCs, embedded controllers and software systems.

TGW Insights

After trying multiple database systems, TGW Logistics moved to CrateDB for its ability to aggregate different data formats and ability to query this information without much hassle.

In the second presentation, you will learn how TGW leverages CrateDB to build digital twins of physical warehouses around the world.

• Fixing data silos in a high-speed logistics environment

• Challenges of Storing and Analyzing Industrial Data

What’s inside

• The Complexity of IoT Data: An examination of the unique properties of industrial IoT data, including slow-moving structured information and high-frequency measurements.

• Challenges and Solutions: Discussion of the difficulties in data storage, retention, and integration posed by this complexity, and how CrateDB provides a targeted solution.

• Real-World Applications: Exploration of actual customer use cases to illustrate how CrateDB can be applied in various industrial scenarios.