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GridTables: A One-Size-Fits-Most H2TAP Data Store

dc.contributor.authorPinnecke, Marcus
dc.contributor.authorCampero Durand, Gabriel
dc.contributor.authorBroneske, David
dc.contributor.authorZoun, Roman
dc.contributor.authorSaake, Gunter
dc.date.accessioned2021-05-04T09:36:34Z
dc.date.available2021-05-04T09:36:34Z
dc.date.issued2020
dc.description.abstractHeterogeneous Hybrid Transactional Analytical Processing ( $$\mathrm{H}^{2}$$ H 2 TAP) database systems have been developed to match the requirements for low latency analysis of real-time operational data. Due to technical challenges, these systems are hard to architect, non-trivial to engineer, and complex to administrate. Current research has proposed excellent solutions to many of those challenges in isolation – a unified engine enabling to optimize performance by combining these solutions is still missing. In this concept paper, we suggest a highly flexible and adaptive data structure (called gridtable ) to physically organize sparse but structured records in the context of $$\mathrm{H}^{2}$$ H 2 TAP. For this, we focus on the design of an efficient highly-flexible storage layout that is built from scratch for mixed query workloads. The key challenges we address are: (1) partial storage in different memory locations, and (2) the ability to optimize for mixed OLTP-/OLAP access patterns. To guarantee safe and well-specified data definition or manipulation, as well as fast querying with no compromises on performance, we propose two dedicated access paths to the storage. In this paper, we explore the architecture and internals of gridtables showing design goals, concepts and trade-offs. We close this paper with open research questions and challenges that must be addressed in order to take advantage of the flexibility of our solution.de
dc.identifier.doi10.1007/s13222-019-00330-x
dc.identifier.pissn1610-1995
dc.identifier.urihttp://dx.doi.org/10.1007/s13222-019-00330-x
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/36390
dc.publisherSpringer
dc.relation.ispartofDatenbank-Spektrum: Vol. 20, No. 1
dc.relation.ispartofseriesDatenbank-Spektrum
dc.subjectDatabase Management
dc.subjectHeterogeneous Databases
dc.subjectHTAP
dc.subjectPhysical Database Design
dc.subjectRelational Databases
dc.titleGridTables: A One-Size-Fits-Most H2TAP Data Storede
dc.typeText/Journal Article
gi.citation.endPage56
gi.citation.startPage43

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