Quick recognition of highly complex patterns.

Relational databases reach their performance limits when dealing with complex applications with large amounts of unstructured data. The result is that response times quickly increase and data cannot be processed in real time. Graph Data and Graph Data Bases, on the other hand, don’t suffer performance losses when dealing with large amounts of entangled data sets. They are especially well-suited for large amounts of strongly connected (real-time) data and unstructured data volumes that don’t fit into any relational structure or table. Laborious calculations are not needed for these data relations because they can be easily tracked through the available structures. A vast amount of direct relations between individual pieces of information can be displayed this way. Both in social or logistical networks and computer networks and telecommunications systems, the information is already available as a network and can be immediately implemented as a graph. This way, correlations and dependencies can quickly be displayed. Based on this, new services can be developed and existing ones can be improved.

  • unlimited flexibility and expandability
  • more precise display of reality
  • can be extended contextually by adding data
  • flexible data modelling
  • short response time through parallelisation of queries
  • analytical visualisation of complex correlations
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Your data analysis with Graph Data

We support you with the technical and methodical conception, the selection and application of custom-fit modelling approaches, and the systematic evaluation of gained insights. Our services offer you a way to benefit from Graph Data Technology.

Our services regarding Graph Data:

  • Development of graph-based data models
  • Development of graph databases and graph visualisations
  • Graphs for Hadoop
  • Graphs for Qlik

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