Performance Analysis in Temporal Database Applied to the Electrical Power Data Scenario

• Vitor O. Santos Federal University of Technology - Paraná (UTFPR)
• Viviane Dal Molin Federal University of Technology - Paraná (UTFPR) https://orcid.org/0000-0002-7602-723X
• Jefferson Tales Oliva Federal University of Technology - Paraná (UTFPR) https://orcid.org/0000-0003-1574-1293
• Ives Renê Venturini Pola Federal University of Technology - Paraná (UTFPR) https://orcid.org/0000-0001-7300-7535

DOI: https://doi.org/10.5753/sbbd.2024.240532

Abstract

This study evaluates the performance of three temporal database management systems (TDBMS) — TimescaleDB, TDengine, and Druid — in managing electrical energy data. The results of read and write tests indicate that, although no single solution outperforms the others in all tests, each offers unique advantages depending on the specific workload requirements. TimescaleDB excels in high-concurrency environments, TDengine is more efficient in scenarios with less complex relational data management needs, and Druid is better suited for situations where analytical query performance is crucial.

Keywords: Database Management System Benchmarking Time Series

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