Graph Databases in the Manufacturing Industry
In recent times, graph databases have gained much popularity thanks to their ease in modeling data whose nature requires expressing a large number of heterogeneous connections. In that sense, the use of graph database management systems such as neo4j, orientdb, arangodb has become popular.
The great advantage of graph databases over traditional models based on the relational model is that graph databases are specifically designed to model a number of problems that require specifying connections between entities.
In this sense, we have been working in the manufacturing domain. The manufacturing industry requires systems that allow to trace the products they produce in an effective and efficient way. The reason is to ensure quality control as well as to identify if there have been any anomalies in any part of the manufacturing process, so that the affected parts can be identified as soon as possible.
In our article [1], we describe the problem faced by one of our partners, as well as describe the design and implementation phases of the solution based on graph databases. It is very likely that in the next years more solutions will appear in this field, since the problems to be solved are quite important.
References
[1] Martinez-Gil J., Stumpner R., Lettner C., Pichler M., Fragner W. (2019)
Design and Implementation of a Graph-Based Solution for Tracking
Manufacturing Products. ADBIS 2019. Communications in
Computer and Information Science, vol 1064. Springer, Cham