The increasing need for managing big data has led the emergence of advanced database management systems. There has been increased efforts aimed at evaluating the performance and scalability of NoSQL and Relational databases hosted by either private or public cloud datacenters. However, there has been little work on evaluating the performance and scalability of these databases in hybrid clouds, where the distance between private and public cloud datacenters can be one of the key factors that can affect their performance. Hence, in this paper, we present a detailed evaluation of throughput, scalability, and VMs size vs. VMs number for six modern databases in a hybrid cloud, consisting of a private cloud in Adelaide and Azure based datacenter in Sydney, Mumbai, and Virginia regions. Based on results, as the distance between private and public clouds increases, the throughput performance of most databases reduces. Second, MongoDB obtains the best throughput performance, followed by MySQL C luster, whilst Cassandra exposes the most fluctuation in through performance. Third, vertical scalability improves the throughput of databases more than the horizontal scalability. Forth, exploiting bigger VMs rather than more VMs with less cores can increase throughput performance for Cassandra, Riak, and Redis.
翻译：由于对管理大数据的需求日益增加,因此出现了先进的数据库管理系统,因此,我们更加努力地评价由私营或公共云中数据中心托管的NSQL和关系数据库的性能和可扩缩性,然而,在评价混合云层中这些数据库的性能和可扩缩性方面,没有做多少工作,在混合云层中,私人和公共云层数据中心之间的距离可能是影响其性能的关键因素之一。因此,在本文件中,我们详细评价了混合云层中六个现代数据库的吞吐量、可扩缩性和VMS大小与VMs编号,包括悉尼、孟买和弗吉尼亚地区基于Adelaide和Azure数据中心的私人云层。根据结果,随着私人和公共云层之间的距离增加,大多数数据库的吞吐量性能下降。第二,MongoDB获得了最佳的吞吐性表现,随后是MySQL C光度,而Csanier则通过性能暴露了最大的波动。第三,垂直缩缩性使数据库的吞吐量比水平高,利用VMS和RDMS的性能增加。
相关内容
微信扫码咨询专知VIP会员