A disk based stream oriented approach for storing big data

Peter Membrey, Keith C. C. Chan, Y. Demchenko
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引用次数: 7

Abstract

This paper proposes an extension to the generally accepted definition of Big Data and from this extended definition proposes a specialized database design for storing high throughput data from low-latency sources. It discusses the challenges a financial company faces with regards to processing and storing data and how existing database technologies are unsuitable for this niche task. A prototype database called CakeDB is built using a stream oriented, disk based storage design and insert throughput tests are conducted to demonstrate how effectively such a design would handle high throughput data as per the use case.
存储大数据的基于磁盘的面向流的方法
本文提出了对大数据普遍接受的定义的扩展,并从这个扩展的定义提出了一个专门的数据库设计,用于存储来自低延迟源的高吞吐量数据。它讨论了金融公司在处理和存储数据方面面临的挑战,以及现有的数据库技术如何不适合这一利基任务。使用面向流、基于磁盘的存储设计构建了一个名为CakeDB的原型数据库,并进行了插入吞吐量测试,以演示这种设计如何有效地处理高吞吐量数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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