Understanding the Performance-Energy Tradeoffs of Object-Relational Mapping Frameworks

• Main Authors: Bonvoisin, Alexandre, Quinton, Clément, Rouvoy, Romain
• Other Authors: Self-adaptation for distributed services and large software systems (SPIRALS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Ipek Ozkaya, Fabio Palomba, ANR-21-CE25-0022,DISTILLER,Service de recommandation pour des logiciels en ligne plus durables(2021), ANR-19-CE25-0003,Koala,Configurations d'environnements fog large-échelle(2019), ANR-23-PECL-0003,CARECloud,Comprendre, Améliorer, Réduire les impacts Environnementaux du Cloud computing(2023)
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2024
• Subjects: ORM Frameworks; Energy consumption; Performance; [INFO]Computer Science [cs]; Rovaniemi
• Online Access: https://inria.hal.science/hal-04401643; https://inria.hal.science/hal-04401643/document; https://inria.hal.science/hal-04401643/file/SANER_24-2.pdf

International audience Object-Relational Mapping (ORM) frameworks are the cornerstone of online services. To reply to incoming requests, these services often rely on these frameworks as a convenient data access layer. However, such frameworks might also be the source of performance inefficiency when configured and used inappropriately. This paper, therefore, compares different configurations of state-of-the-art Java-based ORM frameworks to unveil their performance efficiency, traditionally evaluated through metrics such as execution time and memory usage. However, rising environmental concerns have brought energy consumption to the forefront of the conversation. Beyond performance-centric measurements, we shed light on the energy consumption of these building blocks and explore the trade-offs that conceal the expected quality of service and environmental concerns. Our empirical results, obtained with an ORM-based version of the reference Transaction Processing Performance Council benchmark C (TPC-C) benchmark, highlight that the adoption of an ORM should be carefully configured by developers to leverage the resources offered by underlying databases.