Comparative analysis of efficient methods for storing unstructured data into database with accent on performance

Jasmin Azemovic, Denis Music
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引用次数: 3

Abstract

the management of unstructured data is recognized as one of the major unsolved problems in the information technology (IT) industry, the main reason being that the tools and techniques that have proved so successful transforming structured data into business intelligence and actionable information simply don't work when it comes to unstructured data. This unstructured data is often stored outside the database, separate from its structured data. This separation can cause data management complexities. Or, if the data is associated with structured storage, the file streaming capabilities and performance can be limited. User data is produced and generated on big scale where measurement is hundreds of MB or even couple of GB per user per day. Efficient method for storing and accessing those kinds of data is imperative in modern information society. In this paper we are presenting results of research on using different data types for storing unstructured data within database and classic file system. Research is inspired with current situation in modern information society.
以性能为重点的非结构化数据存储方法的比较分析
非结构化数据的管理被认为是信息技术(IT)行业中未解决的主要问题之一,其主要原因是,将结构化数据成功地转换为商业智能和可操作信息的工具和技术在处理非结构化数据时根本不起作用。这些非结构化数据通常存储在数据库之外,与其结构化数据分开。这种分离会导致数据管理的复杂性。或者,如果数据与结构化存储相关联,则文件流功能和性能可能会受到限制。用户数据的产生和生成是大规模的,每个用户每天的测量值为数百MB甚至几GB。在现代信息社会中,有效的存储和访问这些数据的方法是必不可少的。本文介绍了在数据库和经典文件系统中使用不同数据类型存储非结构化数据的研究结果。研究灵感来源于现代信息社会的现状。
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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