Database Reference
In-Depth Information
Chapter 13
Querying Graph Databases:
An Overview
Sherif Sakr
University of New South Wales, Australia
Ghazi Al-Naymat
University of New South Wales, Australia
ABSTRACT
Recently, there has been a lot of interest in the application of graphs in different domains. Graphs have
been widely used for data modeling in different application domains such as: chemical compounds,
protein networks, social networks, and Semantic Web. Given a query graph, the task of retrieving related
graphs as a result of the query from a large graph database is a key issue in any graph-based applica-
tion. This has raised a crucial need for efficient graph indexing and querying techniques. This chapter
provides an overview of different techniques for indexing and querying graph databases. An overview of
several proposals of graph query language is also given. Finally, the chapter provides a set of guidelines
for future research directions.
INTRODUCTION
The field of graph databases and graph query processing has received a lot of attention due to the
constantly increasing usage of graph data structure for representing data in different domains such as:
chemical compounds (Klinger & Austin, 2005), multimedia databases (Lee et al., 2005), social networks
(Cai et al., 2005), protein networks (Huan et al., 2004) and semantic web (Manola & Miller, 2004). To
effectively understand and utilize any collection of graphs, a graph database that efficiently supports
elementary querying mechanisms is crucially required. Hence, determining graph database members
which constitute the answer set of a graph query
q
from a large graph database is a key performance issue
