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Survey of NoSQL Database Engines for Big Data

机译:大数据NoSQL数据库引擎调查

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摘要

Cloud computing is a paradigm shift that provides computing over Internet. With growing outreach of Internet in the lives of people, everyday large volume of data is generated from different sources such as cellphones, electronic gadgets, e-commerce transactions, social media, and sensors. Eventually, the size of generated data is so large that it is also referred as Big Data. Companies harvesting business opportunities in digital world need to invest their budget and time to scale their IT infrastructure for the expansion of their businesses. The traditional relational databases have limitations in scaling for large Internet scale distributed systems. To store rapidly expanding high volume Big Data efficiently, NoSQL data stores have been developed as an alternative solution to the relational databases.The purpose of this thesis is to provide a holistic overview of different NoSQL data stores. We cover different fundamental principles supporting the NoSQL data store development. Many NoSQL data stores have specific and exclusive features and properties. They also differ in their architecture, data model, storage system, and fault tolerance abilities. This thesis describes different aspects of few NoSQL data stores in detail.The thesis also covers the experiments to evaluate and compare the performance of different NoSQL data stores on a distributed cluster. In the scope of this thesis, HBase, Cassandra, MongoDB, and Riak are four NoSQL data stores selected for the benchmarking experiments.
机译:云计算是一种范式转变,可通过Internet提供计算。随着人们生活中互联网的日益普及,每天从不同的来源(例如手机,电子小工具,电子商务交易,社交媒体和传感器)产生大量数据。最终,生成的数据的大小是如此之大,以至于也被称为大数据。在数字世界中收获商机的公司需要投入预算和时间来扩展其IT基础架构以扩展业务。传统的关系数据库在扩展大型Internet分布式系统方面存在局限性。为了有效地快速存储快速增长的大容量大数据,已经开发出NoSQL数据存储作为关系数据库的替代解决方案。本文的目的是提供各种NoSQL数据存储的整体概述。我们介绍了支持NoSQL数据存储开发的不同基本原理。许多NoSQL数据存储都具有特定且排他的功能和属性。它们在体系结构,数据模型,存储系统和容错能力方面也有所不同。本文详细介绍了少数NoSQL数据存储的不同方面。本文还涵盖了评估和比较分布式集群上不同NoSQL数据存储性能的实验。在本文的范围内,HBase,Cassandra,MongoDB和Riak是四个用于基准测试的NoSQL数据存储。

著录项

  • 作者

    Singh Kuldeep;

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  • 年度 2015
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  • 原文格式 PDF
  • 正文语种 en
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