On the Performance of Three In-Memory Data Systems for On Line Analytical Processing

Ionut Hrubaru () and Marin Fotache ()

Informatica Economica, 2017, vol. 21, issue 1, 5-15

Abstract: In-memory database systems are among the most recent and most promising Big Data technologies, being developed and released either as brand new distributed systems or as extensions of old monolith (centralized) database systems. As name suggests, in-memory systems cache all the data into special memory structures. Many are part of the NewSQL strand and target to bridge the gap between OLTP and OLAP into so-called Hybrid Transactional Analytical Systems (HTAP). This paper aims to test the performance of using such type of systems for TPCH analytical workloads. Performance is analyzed in terms of data loading, memory footprint and execution time of the TPCH query set for three in-memory data systems: Oracle, SQL Server and MemSQL. Tests are subsequently deployed on classical on-disk architectures and results compared to in-memory solutions. As in-memory is an enterprise edition feature, associated costs are also considered.

Keywords: In Memory Databases; OLAP; Analytical Workload; TPCH (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:aes:infoec:v:21:y:2017:i:1:p:5-15

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