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Criteria to Compare Cloud Computing with Current Database Technology

机译:将云计算与当前数据库技术进行比较的标准

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After Google published their first paper on their software infrastructure in October 2003, the open-source community quickly began working on similar free solutions. Yahoo! is now able to process terabytes of data daily using Hadoop, which is a scalable distributed file system and an open-source implementation of Google's MapReduce. HBase, a distributed database that uses Hadoop, enables the reliable storage of structured data, just like Google's Bigtable which powers applications like Google Maps and Google Analytics, to name only two. Many companies are tempted to use these technologies, but it is currently difficult to compare today's systems with systems built on top of HBase. This paper presents this new technology and, a list of proposed comparison elements to existing database technology as well as proposed comparison assessment criteria.
机译:Google于2003年10月发表有关其软件基础结构的第一篇论文后,开源社区迅速开始研究类似的免费解决方案。雅虎!现在可以使用Hadoop每天处理TB级数据,而Hadoop是可扩展的分布式文件系统,是Google MapReduce的开源实现。 HBase是使用Hadoop的分布式数据库,可实现结构化数据的可靠存储,就像Google的Bigtable一样,该表为诸如Google Maps和Google Analytics等应用程序提供支持。许多公司都想使用这些技术,但是目前很难将当今的系统与基于HBase构建的系统进行比较。本文介绍了这项新技术,以及与现有数据库技术的拟议比较要素清单以及拟议的比较评估标准。

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