Intelligent data queries for networked systems

7 min reading time, aktualisiert am 15.04.2025

ActiveDB & GQL – Intelligent data queries for networked systems

With the integration of Graph Query Language (GQL), ActiveDB adds a whole new dimension to accessing company data. Whether it’s production, building technology, energy management, or service platforms – wherever there are complex relationships, GQL provides the right answers. Because data only reveals its true value when it is put into context with other data.

Content

After reading this article, you will know:

  • ActiveDB supports MDM and AI by making networked data relationships visible and analyzable with GQL.
  • GQL enables concrete use cases such as energy optimization or production analysis to be implemented efficiently.
  • External data sources can be securely integrated because GQL enables context-related queries within a standardized architecture.

1.

What is GQL and why is it relevant?

GQL (Graph Query Language) is a modern query language for networked data models. Unlike classic SQL queries, GQL not only takes individual data points into account, but also their relationships – for example: “Which component is causing a bottleneck?” or “Which systems are affected by a status change?”

2.

What makes GQL in ActiveDB special?

ActiveDB uses GQL as its central analysis tool – with specific extensions for:

  1. Real-time and time series data
  2. Semantic links such as “part of,” “manufactures,” “controls”
  3. Contextual analysis across system boundaries
  4. Technical metadata in an understandable form

3.

Practical example 1: Energy optimization in buildings

A property manager uses ActiveDB with GQL to monitor building technology in real time. A GQL query returns all rooms with active radiators where the windows are open. Result: Energy losses are immediately detected and documented – the heating system can be adjusted automatically.

4.

Practical example 2: Production optimization in Industry 4.0

A machine manufacturer uses GQL to identify the causes of frequent production stoppages. A single query links sensor values, maintenance histories, and machine relationships. The result: a faulty sensor is identified as the common trigger for several plant shutdowns. Replacing this sensor can significantly improve OEE (Overall Equipment Effectiveness) – and all it takes is a few lines of code.

5.

Your benefits at a glance

Easy dashboard development:
Quick display of cross-object data from ActiveDB.

Less effort:
Simple queries instead of manual searches.

Greater transparency:
Understand how data and systems are really connected.

Act faster:
Data provides a concrete basis for decision-making.

Scalable:
Works for individual machines as well as company-wide platforms.

Open & future-proof:
Fully integrated into the standards-based ActiveDB architecture.

6.

Conclusion

Whether industrial manufacturing, urban infrastructure, or digital business models: With GQL, ActiveDB becomes the control center for data-based decisions. Instead of isolated information, insights are created—networked, contextualized, and action-oriented.

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