Sean R. Spillane, Jeremy Birnbaum, Daniel Bokser, Daniel Kemp, Alan G. Labouseur, Paul W. Olsen, Jayadevan Vijayan, Jeong-Hyon Hwang, Jun-Weon Yoon
{"title":"A demonstration of the G∗ graph database system","authors":"Sean R. Spillane, Jeremy Birnbaum, Daniel Bokser, Daniel Kemp, Alan G. Labouseur, Paul W. Olsen, Jayadevan Vijayan, Jeong-Hyon Hwang, Jun-Weon Yoon","doi":"10.1109/ICDE.2013.6544943","DOIUrl":null,"url":null,"abstract":"The world is full of evolving networks, many of which can be represented by a series of large graphs. Neither the current graph processing systems nor database systems can efficiently store and query these graphs due to their lack of support for managing multiple graphs and lack of essential graph querying capabilities. We propose to demonstrate our system, G*, that meets the new challenges of managing multiple graphs and supporting fundamental graph querying capabilities. G* can store graphs on a large number of servers while compressing these graphs based on their commonalities. G* also allows users to easily express queries on graphs and efficiently executes these queries by sharing computations across graphs. During our demonstrations, conference attendees will run various analytic queries on large, practical data sets. These demonstrations will highlight the convenience and performance benefits of G* over existing database and graph processing systems, the effectiveness of sharing in graph data storage and processing, as well as G*'s scalability.","PeriodicalId":399979,"journal":{"name":"2013 IEEE 29th International Conference on Data Engineering (ICDE)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 29th International Conference on Data Engineering (ICDE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2013.6544943","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
The world is full of evolving networks, many of which can be represented by a series of large graphs. Neither the current graph processing systems nor database systems can efficiently store and query these graphs due to their lack of support for managing multiple graphs and lack of essential graph querying capabilities. We propose to demonstrate our system, G*, that meets the new challenges of managing multiple graphs and supporting fundamental graph querying capabilities. G* can store graphs on a large number of servers while compressing these graphs based on their commonalities. G* also allows users to easily express queries on graphs and efficiently executes these queries by sharing computations across graphs. During our demonstrations, conference attendees will run various analytic queries on large, practical data sets. These demonstrations will highlight the convenience and performance benefits of G* over existing database and graph processing systems, the effectiveness of sharing in graph data storage and processing, as well as G*'s scalability.