Department of Computer Science
Data engineering in graph databases
Graph-structured databases have a wide range of emerging applications, e.g., the Semantic Web, eXtensible Markup Language (XML), biological databases and network topologies. To-date, there has already been voluminous real-world (possibly cyclic and schemaless) graph-structured data. Therefore, data engineering in graph-structured databases has recently received a lot of attention, where there are limitations as well as scope for significant developments. In these databases, there exist many different indexes and different query languages, e.g., XQuery, regular expressions, Web Ontology Langauge and subgraph isomorphism, while there are few graphical user interfaces for effectively querying subgraphs. In this paper, we examine and evaluate the current state of-the-art in graph-structured databases with respect to (i) query languages, (ii) dynamic aspects, (iii) data mining, (iv) graphical user interfaces, and (v) modern computer architecture on graph-structured data. In addition, the incremental maintenance of graph indexes/views will be addressed. © 2011 Springer Science+Business Media B.V.
assessment, computer architecture, data engineering, data mining, Graph databases, GUI, query formalisms, survey, updates
Source Publication Title
Computer and Information Sciences: Proceedings of the 25th International Symposium on Computer and Information Sciences
London, United Kingdom
Link to Publisher's Edition
Choi, Byron, Haibo Hu, Jianliang Xu, William K. W. Cheung, Chun-Hung Li, and Jiming Liu. "Data engineering in graph databases." Computer and Information Sciences: Proceedings of the 25th International Symposium on Computer and Information Sciences (2010): 127-132.