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DeLorean: A Storage Layer to Analyze Physical Data at Scale

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dc.contributor.authorKußmann, Michael
dc.contributor.authorBerens, Maximilian
dc.contributor.authorEitschberger, Ulrich
dc.contributor.authorKilic, Ayse
dc.contributor.authorLindemann, Thomas
dc.contributor.authorMeier, Frank
dc.contributor.authorNiet, Ramon
dc.contributor.authorSchellenberg, Margarete
dc.contributor.authorStevens, Holger
dc.contributor.authorWishahi, Julian
dc.contributor.authorSpaan, Bernhard
dc.contributor.authorTeubner, Jens
dc.contributor.editorMitschang, Bernhard
dc.contributor.editorNicklas, Daniela
dc.contributor.editorLeymann, Frank
dc.contributor.editorSchöning, Harald
dc.contributor.editorHerschel, Melanie
dc.contributor.editorTeubner, Jens
dc.contributor.editorHärder, Theo
dc.contributor.editorKopp, Oliver
dc.contributor.editorWieland, Matthias
dc.date.accessioned2017-06-20T20:24:32Z
dc.date.available2017-06-20T20:24:32Z
dc.date.issued2017
dc.description.abstractModern research in high energy physics depends on the ability to analyse massive volumes of data in short time. In this article, we report on DeLorean, which is a new system architecture for high-volume data processing in the domain of particle physics. DeLorean combines the simplicity and performance of relational database technology with the massive scalability of modern cloud execution platforms (Apache Drill for that matter). Experiments show a four-fold performance improvement over state-of-the-art solutions.en
dc.identifier.isbn978-3-88579-659-6
dc.identifier.pissn1617-5468
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW 2017)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-265
dc.subjectdata analysis
dc.subjectbig data
dc.subjectLHCb
dc.subjectdatabase
dc.subjectdistributed computing
dc.subjectmodern hardware
dc.subjectnuclear physics
dc.titleDeLorean: A Storage Layer to Analyze Physical Data at Scaleen
dc.typeText/Conference Paper
gi.citation.endPage422
gi.citation.startPage413
gi.conference.date6.-10. März 2017
gi.conference.locationStuttgart
gi.conference.sessiontitleScientific Data and Hardware

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