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Comparative Study of Open Source Database Management Systems to Enable Predictive Maintenance of Autonomous Guided Vehicles

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18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) (SOCO 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 749))

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Abstract

A number of open source database systems have been researched and assessed in this work for the purpose of choosing the optimum technology to implement predictive maintenance systems for industrial Autonomous Guided Vehicles. An application-driven technique has been suggested as a way to achieve it. The use case and its specifications are first outlined and listed. The top five most popular time series database systems are then contrasted based on a variety of technical metrics including software support, community support, and different technical features. From this analysis the best two options are selected (InfluxDB and TimeScale DB). The performance of these two is then further examined, taking into account performance indicators like insert time, throughput, and resource consumption. Results show that TimeScale DB provides a higher performance but demands considerably more resources.

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Acknowledgement

This work was partially supported by the European Commission, under European Project 5G-Induce, grant number 101016941.

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Authors and Affiliations

  1. Department of Digitalization, University of Burgos, Burgos, Spain

    Gonzalo Burgos, Jesús Enrique Sierra-García & Bruno Baruque-Zanón

Authors
  1. Gonzalo Burgos
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  2. Jesús Enrique Sierra-García
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  3. Bruno Baruque-Zanón
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Corresponding author

Correspondence to Gonzalo Burgos .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. School of Industrial, Computer, University of Leon, León, Spain

    Hilde Pérez García

  3. Department of Mechanical Engineering, University of La Rioja, Logroño, Spain

    Francisco Javier Martínez de Pisón

  4. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  5. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Alicia Troncoso Lora

  6. Applied Computational Intelligence, University of Burgos, Burgos, Spain

    Álvaro Herrero

  7. Department of Industrial Engineering, University of A Coruña, A Coruña, Spain

    José Luis Calvo Rolle

  8. Department of Industrial Engineering, University of A Coruña, A Coruña, Spain

    Héctor Quintián

  9. Faculty of Science, University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Cite this paper

Burgos, G., Sierra-García, J.E., Baruque-Zanón, B. (2023). Comparative Study of Open Source Database Management Systems to Enable Predictive Maintenance of Autonomous Guided Vehicles. In: García Bringas, P., et al. 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023). SOCO 2023. Lecture Notes in Networks and Systems, vol 749. Springer, Cham. https://doi.org/10.1007/978-3-031-42529-5_26

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