{"title":"图数据库的数据、存储和索引模型","authors":"S. Srinivasa","doi":"10.4018/978-1-61350-053-8.ch003","DOIUrl":null,"url":null,"abstract":"Management of graph structured data has important applications in several areas. Queries on such data sets are based on structural properties of the graphs, in addition to values of attributes. Answering such queries pose significant challenges, as reasoning about structural properties across graphs are typically intractable problems. This chapter provides an overview of the challenges in designing databases over graph datasets. Different application areas that use graph databases, pose their own unique set of challenges, making the task of designing a generic graphoriented DBMS still an elusive goal. The purpose of this chapter is to survey some of the piecemeal solutions that have been proposed to address specific challenges in graph data management and suggest an overall structure in which these different solutions can be meaningfully placed.","PeriodicalId":227251,"journal":{"name":"Graph Data Management","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Data, Storage and Index Models for Graph Databases\",\"authors\":\"S. Srinivasa\",\"doi\":\"10.4018/978-1-61350-053-8.ch003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Management of graph structured data has important applications in several areas. Queries on such data sets are based on structural properties of the graphs, in addition to values of attributes. Answering such queries pose significant challenges, as reasoning about structural properties across graphs are typically intractable problems. This chapter provides an overview of the challenges in designing databases over graph datasets. Different application areas that use graph databases, pose their own unique set of challenges, making the task of designing a generic graphoriented DBMS still an elusive goal. The purpose of this chapter is to survey some of the piecemeal solutions that have been proposed to address specific challenges in graph data management and suggest an overall structure in which these different solutions can be meaningfully placed.\",\"PeriodicalId\":227251,\"journal\":{\"name\":\"Graph Data Management\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Graph Data Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/978-1-61350-053-8.ch003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Graph Data Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-61350-053-8.ch003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data, Storage and Index Models for Graph Databases
Management of graph structured data has important applications in several areas. Queries on such data sets are based on structural properties of the graphs, in addition to values of attributes. Answering such queries pose significant challenges, as reasoning about structural properties across graphs are typically intractable problems. This chapter provides an overview of the challenges in designing databases over graph datasets. Different application areas that use graph databases, pose their own unique set of challenges, making the task of designing a generic graphoriented DBMS still an elusive goal. The purpose of this chapter is to survey some of the piecemeal solutions that have been proposed to address specific challenges in graph data management and suggest an overall structure in which these different solutions can be meaningfully placed.