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

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.