Comparative Analysis of Graph Databases for Git Data
In past decades, the requirements that database management systems (DBMSs) must achieve have become increasingly stringent (speed, data volume). This increase in complexity led to the development of a wide range of non-relational databases strategies, each one suited for specific scenarios. In this...
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| Veröffentlicht in: | Journal of physics. Conference series 2021-06, Vol.1944 (1), p.12004 |
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| creator | Falcão, Thiago A. Furtado, Phillip M. Queiroz, Jordan S. Matos, Paulo J. O. Antunes, Tiago F. Carvalho, Frederico S. Fonseca, Paulo C. R. Giuntini, Felipe T. |
| description | In past decades, the requirements that database management systems (DBMSs) must achieve have become increasingly stringent (speed, data volume). This increase in complexity led to the development of a wide range of non-relational databases strategies, each one suited for specific scenarios. In this context, Graph Database Management Systems (GDBMSs) became popular to represent social networks and other domains that can be intuitively represented as graph-like structures. In this paper, we represent Version Control System data, specifically Git, from a large software project in a graph structure and compared three popular GDBMSs:
Neo4j
,
Janus Graph
and
Dgraph
. We evaluated read/write operations performance for common activities, such as inserting new commits into the graph and retrieving the complete commit history of a specific project. With this contribution, researches and engineers may choose, assertively, the better solution for their needs. |
| doi_str_mv | 10.1088/1742-6596/1944/1/012004 |
| format | Article |
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Neo4j
,
Janus Graph
and
Dgraph
. We evaluated read/write operations performance for common activities, such as inserting new commits into the graph and retrieving the complete commit history of a specific project. With this contribution, researches and engineers may choose, assertively, the better solution for their needs.</description><identifier>ISSN: 1742-6588</identifier><identifier>EISSN: 1742-6596</identifier><identifier>DOI: 10.1088/1742-6596/1944/1/012004</identifier><language>eng</language><publisher>Bristol: IOP Publishing</publisher><subject>Data base management systems ; Graphical representations ; Physics ; Relational data bases ; Social networks ; Version control</subject><ispartof>Journal of physics. Conference series, 2021-06, Vol.1944 (1), p.12004</ispartof><rights>Published under licence by IOP Publishing Ltd</rights><rights>2021. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2584-887da030ee3d40ca50d450519def8d1b29cc2e3929a534fec4b8f135a09cb72e3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/1742-6596/1944/1/012004/pdf$$EPDF$$P50$$Giop$$Hfree_for_read</linktopdf><link.rule.ids>314,776,780,27903,27904,38847,38869,53818,53845</link.rule.ids></links><search><creatorcontrib>Falcão, Thiago A.</creatorcontrib><creatorcontrib>Furtado, Phillip M.</creatorcontrib><creatorcontrib>Queiroz, Jordan S.</creatorcontrib><creatorcontrib>Matos, Paulo J. O.</creatorcontrib><creatorcontrib>Antunes, Tiago F.</creatorcontrib><creatorcontrib>Carvalho, Frederico S.</creatorcontrib><creatorcontrib>Fonseca, Paulo C. R.</creatorcontrib><creatorcontrib>Giuntini, Felipe T.</creatorcontrib><title>Comparative Analysis of Graph Databases for Git Data</title><title>Journal of physics. Conference series</title><addtitle>J. Phys.: Conf. Ser</addtitle><description>In past decades, the requirements that database management systems (DBMSs) must achieve have become increasingly stringent (speed, data volume). This increase in complexity led to the development of a wide range of non-relational databases strategies, each one suited for specific scenarios. In this context, Graph Database Management Systems (GDBMSs) became popular to represent social networks and other domains that can be intuitively represented as graph-like structures. In this paper, we represent Version Control System data, specifically Git, from a large software project in a graph structure and compared three popular GDBMSs:
Neo4j
,
Janus Graph
and
Dgraph
. We evaluated read/write operations performance for common activities, such as inserting new commits into the graph and retrieving the complete commit history of a specific project. 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Neo4j
,
Janus Graph
and
Dgraph
. We evaluated read/write operations performance for common activities, such as inserting new commits into the graph and retrieving the complete commit history of a specific project. With this contribution, researches and engineers may choose, assertively, the better solution for their needs.</abstract><cop>Bristol</cop><pub>IOP Publishing</pub><doi>10.1088/1742-6596/1944/1/012004</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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| source | IOP Publishing Free Content; Institute of Physics IOPscience extra; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection; Free Full-Text Journals in Chemistry |
| subjects | Data base management systems Graphical representations Physics Relational data bases Social networks Version control |
| title | Comparative Analysis of Graph Databases for Git Data |
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