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SAP HANA Vora: A Distributed Computing Platform for Enterprise Data Lakes

dc.contributor.authorSengstock, Christian
dc.contributor.authorMathis, Christian
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.accessioned2017-06-20T20:24:34Z
dc.date.available2017-06-20T20:24:34Z
dc.date.issued2017
dc.description.abstractBusinesses are increasingly leveraging the power of Big Data to improve their services and products. We call the infrastructure to process and manage the heterogenous kinds of data their “data lakes”. Data lakes are used to store and process massive streams of sensor data, service data, collected or generated media, archived enterprise data, and massive transactional databases, among others. Such infrastructures are often realized by Hadoop clusters and low-cost persistence layers, such as S3 or SWIFT data stores. SAP HANA Vora is a distributed computing platform that sits on top of Data Lakes and was developed to build a basis layer for upcoming Big Data applications in the enterprise. It provides high-performance in-memory data processing and management capabilities, is easily extensible by new computing engines, extends the existing Big Data software stack, and integrates with the existing enterprise IT by design. We present an architectural overview of the system.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.titleSAP HANA Vora: A Distributed Computing Platform for Enterprise Data Lakesen
dc.typeText/Conference Paper
gi.citation.endPage522
gi.citation.startPage521
gi.conference.date6.-10. März 2017
gi.conference.locationStuttgart
gi.conference.sessiontitleIndustrial Program - Big Data

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