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Enterprise Application-Specific Data Management

机译:企业专用数据管理

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摘要

Enterprise applications are presently built on a 20-year old data management infrastructure that was designed to meet a specific set of requirements for OLTP systems. In the meantime, enterprise applications have become more sophisticated, data set sizes have increased, requirements on the freshness of input data have been strengthened, and the time allotted for completing business processes has been reduced. To meet these challenges, enterprise applications have become increasingly complicated to make up for short-comings in the data management infrastructure. To address this issue we investigate recent trends in data management such as main memory databases, column stores and compression techniques with regards to the workload requirements and data characteristics derived from actual customer systems. We show that a main memory column store is better suited for to days enterprise systems, which we validate by using SAPȁ9;s Net Weaver Business Warehouse Accelerator and a realistic set of data from an inventory management application.
机译:当前,企业应用程序建立在已有20年历史的数据管理基础结构上,该基础结构旨在满足OLTP系统的一组特定要求。同时,企业应用程序变得越来越复杂,数据集的大小增加了,对输入数据的新鲜度的要求得到了增强,并且减少了完成业务流程所需的时间。为了应对这些挑战,企业应用程序变得越来越复杂,以弥补数据管理基础架构中的缺点。为了解决这个问题,我们研究了数据管理方面的最新趋势,例如主内存数据库,列存储和压缩技术等方面的工作负载需求和源自实际客户系统的数据特征。我们表明,主内存列存储更适合于当今的企业系统,我们通过使用SAPȁ9的Net Weaver Business Warehouse Accelerator和库存管理应用程序中的一组实际数据进行了验证。

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