A benchmark study of modern distributed databases is an important source of information to select the right technology for managing data in the cloud-edge paradigms. To make the right decision, it is required to conduct an extensive experimental study on a variety of hardware infrastructures. While most of the state-of-the-art studies have investigated only response time and scalability of distributed databases, focusing on other various metrics (e.g., energy, bandwidth, and storage consumption) is essential to fully understand the resources consumption of the distributed databases. Also, existing studies have explored the response time and scalability of these databases either in private or public cloud. Hence, there is a paucity of investigation into the evaluation of these databases deployed in a hybrid cloud, which is the seamless integration of public and private cloud. To address these research gaps, in this paper, we investigate energy, bandwidth and storage consumption of the most used and common distributed databases. For this purpose, we have evaluated four open-source databases (Cassandra, Mongo, Redis and MySQL) on the hybrid cloud spanning over local OpenStack and Microsoft Azure, and a variety of edge computing nodes including Raspberry Pi, a cluster of Raspberry Pi, and low and high power servers. Our extensive experimental results reveal several helpful insights for the deployment selection of modern distributed databases in edge-cloud environments.
翻译:现代分布式数据库的基准研究是选择管理云端模式数据的适当技术的重要信息来源。为了做出正确决定,需要对各种硬件基础设施进行广泛的实验性研究。虽然大多数最新研究只调查分布式数据库的反应时间和可扩展性,重点是其他各种指标(例如能源、带宽和存储消耗),对于充分了解分布式数据库的资源消耗至关重要。此外,现有研究探索了这些数据库在私人或公共云层中的反应时间和可扩展性。因此,对在混合云层中部署的这些数据库的评价缺乏调查,这种云层是公共和私人云层的无缝整合。为弥补这些研究差距,我们在本文中只调查使用最多的和共同分布式数据库的能源、带宽和储存消耗情况。为此目的,我们评估了四个开放源数据库(Cassandra、Mongo、Redis和MySQL),关于覆盖本地 OpenStack和Microsoft Azure的混合云层云层云层反应和高端层服务器,包括用于在Pirebreal Expreal Explain Exlishal Ex Ex-roal Explain Exirestal Explain Explain Explain 和多层的高级服务器,我们高端和高端的高级服务器,以及高端选择,我们对Pial Explain Explain Explain Explain Explabrebreablectional Export Export Export Export Explal Explal Explal Ex Explal Exdial Explal Explal Explal Explabal Exmal Expl Explal Explal Exmal Exmal Explabal Explal Explal Expl Exal Expl Exal Exal Exal Exal Explal Explal Explabal Explal Explabal Explal Explal Explal Explal Exal Exal Exal Exal Explal Explal Explal Explal Explal Exmal Exal 和多