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  2. School of Engineering
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  4. Publikationen School of Engineering
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dc.contributor.authorStockinger, Kurt-
dc.contributor.authorBödi, Richard-
dc.contributor.authorHeitz, Jonas-
dc.contributor.authorWeinmann, Thomas Oskar-
dc.date.accessioned2018-03-26T14:39:36Z-
dc.date.available2018-03-26T14:39:36Z-
dc.date.issued2017-
dc.identifier.issn0169-023Xde_CH
dc.identifier.issn1872-6933de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/4264-
dc.description.abstractNoSQL data stores have recently gained popularity as an alternative to relational database management systems since they typically do not require a fixed schema and scale well for large data sets. These systems have often been tuned to a number of very specific operations such as writing or reading of large data sets. However, none of these novel systems has been demonstrated to efficiently perform multi-dimensional range queries incorporating many boolean operators, a task which is commonly used in scientific data exploration, data warehousing and business analytics. In this paper we introduce ZurichNoSQL (ZNS) – a novel NoSQL main memory store that supports efficient processing of multi-dimensional point queries and range queries. The key idea of ZNS is to store the data in a column format (compressed column storage) similar to systems used in high performance computing. Moreover, the ZNS architecture is based on a set of low-level main memory techniques ensuring that CPU caches are being used efficiently. Our experimental results comparing to popular NoSQL stores such as FastBit, MongoDB and Spark SQL demonstrate that ZNS significantly outperforms these systems in most cases.de_CH
dc.language.isoende_CH
dc.publisherElsevierde_CH
dc.relation.ispartofData & Knowledge Engineeringde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subject.ddc005: Computerprogrammierung, Programme und Datende_CH
dc.titleZNS : efficient query processing with ZurichNoSQLde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
dc.identifier.doi10.1016/j.datak.2017.09.004de_CH
zhaw.funding.euNode_CH
zhaw.issue112de_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end54de_CH
zhaw.pages.start38de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume2017de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedInformation Engineeringde_CH
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Stockinger, K., Bödi, R., Heitz, J., & Weinmann, T. O. (2017). ZNS : efficient query processing with ZurichNoSQL. Data & Knowledge Engineering, 2017(112), 38–54. https://doi.org/10.1016/j.datak.2017.09.004
Stockinger, K. et al. (2017) ‘ZNS : efficient query processing with ZurichNoSQL’, Data & Knowledge Engineering, 2017(112), pp. 38–54. Available at: https://doi.org/10.1016/j.datak.2017.09.004.
K. Stockinger, R. Bödi, J. Heitz, and T. O. Weinmann, “ZNS : efficient query processing with ZurichNoSQL,” Data & Knowledge Engineering, vol. 2017, no. 112, pp. 38–54, 2017, doi: 10.1016/j.datak.2017.09.004.
STOCKINGER, Kurt, Richard BÖDI, Jonas HEITZ und Thomas Oskar WEINMANN, 2017. ZNS : efficient query processing with ZurichNoSQL. Data & Knowledge Engineering. 2017. Bd. 2017, Nr. 112, S. 38–54. DOI 10.1016/j.datak.2017.09.004
Stockinger, Kurt, Richard Bödi, Jonas Heitz, and Thomas Oskar Weinmann. 2017. “ZNS : Efficient Query Processing with ZurichNoSQL.” Data & Knowledge Engineering 2017 (112): 38–54. https://doi.org/10.1016/j.datak.2017.09.004.
Stockinger, Kurt, et al. “ZNS : Efficient Query Processing with ZurichNoSQL.” Data & Knowledge Engineering, vol. 2017, no. 112, 2017, pp. 38–54, https://doi.org/10.1016/j.datak.2017.09.004.


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