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Journal of Software:2019.30(1):127-141

大数据管理系统的历史、现状与未来
杜小勇,卢卫,张峰
(数据工程与知识工程教育部重点实验室(中国人民大学), 北京 100872;中国人民大学 信息学院, 北京 100872)
History, Present, and Future of Big Data Management Systems
DU Xiao-Yong,LU Wei,ZHANG Feng
(Key Laboratory of Data Engineering and Knowledge Engineering, MOE(Renmin University of China), Beijing 100872, China;School of Information, Renmin University of China, Beijing 100872, China)
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Received:July 04, 2018    Revised:August 21, 2018
> 中文摘要: 大数据管理技术正在经历以软件为中心到以数据为中心的计算平台的变迁,传统的关系型数据库管理系统无法满足现在以数据为中心的大数据管理的需求,设计新型大数据管理系统迫在眉睫.首先回顾了数据管理技术的发展历史;之后,从大数据管理的存储、数据模型、计算模式、查询引擎等方面分析了大数据管理系统的现状,指出目前大数据管理系统具有模块化和松耦合的特点,并进一步介绍了大数据管理系统应具备的数据特征、系统特征和应用特征,指出大数据管理系统技术还在快速进化之中,预测未来的大数据管理系统应具备多数据模型并存、多计算模式融合、可伸缩调整、新硬件驱动、自适应调优等特点.
Abstract:Big data management systems are migrating from software-centric computing platforms to data-centric computing platforms, and traditional relational databse management systems (a.b.a. RDBMS) do not entirely meet the need for data-centric data management. Hence, it is urgent to design a new kind of big data management systems. In thisThe paper, we first reviews the history of the development of data management systems. Second, we it analyzes the current situation of big data management systems in terms of data storage, data model, and query engines of big data management systems, and points out that current big data management systems have the characteristics of modularity and loose coupling. After that, the data characteristics and application characteristics of the big data management systems are we introduced the data characteristics and application characteristics of the big data management systems,, and it is pointed out that big data management systems are still rapidly evolving, but do not mature. Finally, the future of big data management systems is we predicted, i.e., the future of big data management systems. Big big data management systems in future should have the characteristics of multiple data models coexistence, multi-computation platform fusion, elastic adjustment, new hardware driven, self-adaptive tuning, and so on.
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基金项目:国家重点研发计划(2018YFB1004401);国家自然科学基金(61732014,61502504,61802412);北京市科技计划(Z171100005117002) 国家重点研发计划(2018YFB1004401);国家自然科学基金(61732014,61502504,61802412);北京市科技计划(Z171100005117002)
Foundation items:National Key Research and Development Program of China (2018YFB1004401); National Natural Science Foundation of China (61732014, 61502504, 61802412); Beijing Municipal Science and Technology Project (Z171100005117002)
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杜小勇,卢卫,张峰.大数据管理系统的历史、现状与未来.软件学报,2019,30(1):127-141

DU Xiao-Yong,LU Wei,ZHANG Feng.History, Present, and Future of Big Data Management Systems.Journal of Software,2019,30(1):127-141