Analytics on Historical Data Using a Clustered Insert-Only In-Memory Column Database
In the field of OLAP and Data Warehousing,column stores and compressed main-memory data storage technology have successfully been implemented in products that enable a significant speed improvement of analytical queries with special performance requirements. We could soon see the majority of analytical workloads move to such main-memory based systems. Having one specialized OLAP DBMS explicitly aimed at performing ad-hoc queries on an ever-growing database requires the capability of an in-memory database to retain historical states so that applications can calculate consistent values based on previous states of the database,a requirement often found in financial and production planning analytical applications. This paper describes Rock,an in-memory analytics cluster based on a column store database,and proposes an architecture for historical query support as well as the prototypical implementation in Rock.
Databases Software-as-a-Service
Jan Schaffner Jens Krüger Stephan Müller Paul Hofmann Alexander Zeier
Hasso Plattner-Institute for IT Systems Engineering at the University of Potsdam,Prof.-Dr.-Helmert-S SAPAG,Dietmar-Hopp-Allee 16,69190 Walldorf,Germany
国际会议
北京
英文
704-708
2009-10-21（万方平台首次上网日期，不代表论文的发表时间）