Vertexica: your relational friend for graph analytics!
In 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 gra...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Association for Computing Machinery (ACM)
2016
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| Online Access: | http://hdl.handle.net/1721.1/100912 https://orcid.org/0000-0001-9184-9058 https://orcid.org/0000-0002-7470-3265 |
| _version_ | 1826194083299721216 |
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| author | Jindal, Alekh Rawlani, Praynaa Wu, Eugene Deshpande, Amol Madden, Samuel R. Stonebraker, Michael |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Jindal, Alekh Rawlani, Praynaa Wu, Eugene Deshpande, Amol Madden, Samuel R. Stonebraker, Michael |
| author_sort | Jindal, Alekh |
| collection | MIT |
| description | In 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. |
| first_indexed | 2024-09-23T09:50:14Z |
| format | Article |
| id | mit-1721.1/100912 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T09:50:14Z |
| publishDate | 2016 |
| publisher | Association for Computing Machinery (ACM) |
| record_format | dspace |
| spelling | mit-1721.1/1009122022-09-30T17:11:30Z Vertexica: your relational friend for graph analytics! Jindal, Alekh Rawlani, Praynaa Wu, Eugene Deshpande, Amol Madden, Samuel R. Stonebraker, Michael Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Jindal, Alekh Rawlani, Praynaa Wu, Eugene Madden, Samuel R. Stonebraker, Michael In 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. 2016-01-19T02:04:41Z 2016-01-19T02:04:41Z 2014-08 Article http://purl.org/eprint/type/ConferencePaper 21508097 http://hdl.handle.net/1721.1/100912 Alekh 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. https://orcid.org/0000-0001-9184-9058 https://orcid.org/0000-0002-7470-3265 en_US http://dx.doi.org/10.14778/2733004.2733057 Proceedings of the VLDB Endowment Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported licence http://creativecommons.org/licenses/by-nc-nd/3.0/ application/pdf Association for Computing Machinery (ACM) MIT web domain |
| spellingShingle | Jindal, Alekh Rawlani, Praynaa Wu, Eugene Deshpande, Amol Madden, Samuel R. Stonebraker, Michael Vertexica: your relational friend for graph analytics! |
| title | Vertexica: your relational friend for graph analytics! |
| title_full | Vertexica: your relational friend for graph analytics! |
| title_fullStr | Vertexica: your relational friend for graph analytics! |
| title_full_unstemmed | Vertexica: your relational friend for graph analytics! |
| title_short | Vertexica: your relational friend for graph analytics! |
| title_sort | vertexica your relational friend for graph analytics |
| url | http://hdl.handle.net/1721.1/100912 https://orcid.org/0000-0001-9184-9058 https://orcid.org/0000-0002-7470-3265 |
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