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In-Memory Databases and Data Aging: How to Handle Cold Data

Not all of your company’s data is accessed frequently, which results in the potential for improvement where performance and costs (TCO) are concerned. In this session, we present a partitioning concept for actual and historical enterprise data that sets the groundwork for efficient OLTP scale-up and OLAP scale-out, thus allowing for further scaling of the performance of columnar in-memory databases while lowering TCO.

The speaker, Stefan Klauck, is a research assistant at the chair of Prof. Hasso Plattner at the Hasso Plattner Institute, Germany. In the research area “In-Memory Data Management for Enterprise Systems“, Stefan and his colleagues conduct research projects with the goal of improving main memory databases for both transactional and analytical queries in a single system. Enterprise databases for mixed workloads enable interactive analytics on transactional data.


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