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dc.contributor.authorJindal, Alekh
dc.contributor.authorRawlani, Praynaa
dc.contributor.authorWu, Eugene
dc.contributor.authorDeshpande, Amol
dc.contributor.authorMadden, Samuel R.
dc.contributor.authorStonebraker, Michael
dc.date.accessioned2016-01-19T02:04:41Z
dc.date.available2016-01-19T02:04:41Z
dc.date.issued2014-08
dc.identifier.issn21508097
dc.identifier.urihttp://hdl.handle.net/1721.1/100912
dc.description.abstractIn this paper, we present Vertexica, a graph analytics tools on top of a relational database, which is user friendly and yet highly efficient. Instead of constraining programmers to SQL, Vertexica offers a popular vertex-centric query interface, which is more natural for analysts to express many graph queries. The programmers simply provide their vertex-compute functions and Vertexica takes care of efficiently executing them in the standard SQL engine. The advantage of using Vertexica is its ability to leverage the relational features and enable much more sophisticated graph analysis. These include expressing graph algorithms which are difficult in vertex-centric but straightforward in SQL and the ability to compose end-to-end data processing pipelines, including pre- and post- processing of graphs as well as combining multiple algorithms for deeper insights. Vertexica has a graphical user interface and we outline several demonstration scenarios including, interactive graph analysis, complex graph analysis, and continuous and time series analysis.en_US
dc.language.isoen_US
dc.publisherAssociation for Computing Machinery (ACM)en_US
dc.relation.isversionofhttp://dx.doi.org/10.14778/2733004.2733057en_US
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported licenceen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/en_US
dc.sourceMIT web domainen_US
dc.titleVertexica: your relational friend for graph analytics!en_US
dc.typeArticleen_US
dc.identifier.citationAlekh Jindal, Praynaa Rawlani, Eugene Wu, Samuel Madden, Amol Deshpande, and Mike Stonebraker. 2014. Vertexica: your relational friend for graph analytics!. Proc. VLDB Endow. 7, 13 (August 2014), 1669-1672.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorJindal, Alekhen_US
dc.contributor.mitauthorRawlani, Praynaaen_US
dc.contributor.mitauthorWu, Eugeneen_US
dc.contributor.mitauthorMadden, Samuel R.en_US
dc.contributor.mitauthorStonebraker, Michaelen_US
dc.relation.journalProceedings of the VLDB Endowmenten_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsJindal, Alekh; Rawlani, Praynaa; Wu, Eugene; Madden, Samuel; Deshpande, Amol; Stonebraker, Mikeen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-9184-9058
dc.identifier.orcidhttps://orcid.org/0000-0002-7470-3265
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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