Systematic Mapping for Big Data Stream Processing Frameworks

dc.authoridKarakaya, Ziya/0000-0003-0233-7312
dc.authorwosidYazici, Ali/Q-5115-2019
dc.authorwosidKarakaya, Ziya/J-8279-2018
dc.contributor.authorAlayyoub, Mohammed
dc.contributor.authorYazici, Ali
dc.contributor.authorKarakaya, Ziya
dc.contributor.otherComputer Engineering
dc.contributor.otherSoftware Engineering
dc.date.accessioned2024-10-06T11:12:26Z
dc.date.available2024-10-06T11:12:26Z
dc.date.issued2016
dc.departmentAtılım Universityen_US
dc.department-temp[Alayyoub, Mohammed] Atilim Univ, Inst Nat & Appl Sci, Ankara, Turkey; [Yazici, Ali; Karakaya, Ziya] Atilim Univ, Fac Engn, Ankara, Turkeyen_US
dc.descriptionKarakaya, Ziya/0000-0003-0233-7312en_US
dc.description.abstractThere has been lots of discussions about the choice of a stream processing framework (SPF) for Big Data. Each of the SPFs has different cutting edge technologies in their steps of processing the data in motion that gives them a better advantage over the others. Even though, the cutting edge technologies used in each stream processing framework might better them, it is still hard to say which framework bests the rest under different scenarios and conditions. in this study, we aim to show trends and differences about several SPFs for Big Data by using the Systematic Mapping (SM) approach. To achieve our objectives, we raise 6 research questions (RQs), in which 91 studies that conducted between 2010 and 2015 were evaluated. We present the trends by classifying the research on SPFs with respect to the proposed RQs which can help researchers to obtain an overview of the field.en_US
dc.description.woscitationindexConference Proceedings Citation Index - Science
dc.identifier.citationcount0
dc.identifier.endpage36en_US
dc.identifier.isbn9781509026418
dc.identifier.startpage31en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14411/9147
dc.identifier.wosWOS:000398535200006
dc.institutionauthorYazıcı, Ali
dc.institutionauthorKarakaya, Ziya
dc.language.isoenen_US
dc.publisherIeeeen_US
dc.relation.ispartof11th International Conference on Digital Information Management (ICDIM) -- SEP 19-21, 2016 -- Porto, PORTUGALen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBig Dataen_US
dc.subjectStreamingen_US
dc.subjectStormen_US
dc.subjectFlinken_US
dc.subjectSparken_US
dc.subjectS4en_US
dc.subjectInfoSphereen_US
dc.titleSystematic Mapping for Big Data Stream Processing Frameworksen_US
dc.typeConference Objecten_US
dc.wos.citedbyCount0
dspace.entity.typePublication
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