# The Graph Traversal Pattern

@inproceedings{Rodriguez2011TheGT,
title={The Graph Traversal Pattern},
author={Michael A. Rodriguez and Peter Neubauer},
booktitle={Graph Data Management},
year={2011}
}
• Published in Graph Data Management 6 April 2010
• Computer Science
A graph is a structure composed of a set of vertices (i.e.nodes, dots) connected to one another by a set of edges (i.e.links, lines). The concept of a graph has been around since the late 19$^\text{th}$ century, however, only in recent decades has there been a strong resurgence in both theoretical and applied graph research in mathematics, physics, and computer science. In applied computing, since the late 1960s, the interlinked table structure of the relational database has been the…
122 Citations

## Figures from this paper

Constructions from Dots and Lines
• Computer Science
ArXiv
• 2010
The world of graphs in computing is explored and situations in which graphical models are beneficial are exposed.
Partitioning Graph Databases - A Quantitative Evaluation
• Computer Science
ArXiv
• 2013
This work evaluates the viability of using graph partitioning algorithms to partition graph databases and found strong correlations were found between theoretic quality metrics and generated network traffic under non-uniform access patterns.
Evaluation of contemporary graph databases
• Computer Science
COMPUTE '14
• 2014
This paper attempts to evaluate several such contemporary Graph Databases from a subjective feature-based and empirical performance-based perspective.
A Hub-based Graph Management for Efficient Repetition Path Traversing
• Computer Science
2021 IEEE International Conference on Big Data and Smart Computing (BigComp)
• 2021
This paper proposes an efficient approach to repeatedly traversing edges belonging to a specific relationship type by distinguishing between hub s and other nodes in a conventional GDB; this GDB aims to enable us to manage a real-world network effectively.
A framework for incremental view graph maintenance
This thesis contributes a modeling language for the effective definition of generalized discrimination networks for incremental graph pattern matching and provides a performance evaluation, which shows that the incremental maintenance algorithm scales, when the graph data becomes large, and the generalized discrimination network structures can outperform Rete network structures in time and space at the same time.
Benchmarking Traversal Operations over Graph Databases
• Computer Science
2012 IEEE 28th International Conference on Data Engineering Workshops
• 2012
This paper addresses the need to compare the performance of different graph databases, and discusses the challenges of developing fair benchmarking methodologies, and describes the design of the graph traversal benchmark and presents its results.
PROPER - A Graph Data Model Based on Property Graphs
• Computer Science, Mathematics
ISIP
• 2015
This work introduces a set of operations that generate new hyper nodes and new hyper edges from old, therefore providing the basis for a query language in PROPER, and shows how certain semantic constructs such as equational constraints and ISA relationships can be defined in this model.
Graph databases: A survey
An overview of the different type of graph databases, applications, and comparison between their models based on some properties is given.
Graph databases: A survey
• Rohit kumar Kaliyar
• Computer Science
International Conference on Computing, Communication & Automation
• 2015
An overview of the different type of graph databases, applications, and comparison between their models based on some properties is given.
Graph Databases
• Computer Science
Encyclopedia of Big Data Technologies
• 2019
This paper defines the Data Definition Language (DDL) that contains extensional definitions as well as intentional definitions, and Data Manipulation Language (DML) that is used to pose queries that are not easily answer by SQL language, and implements a new type of database structure, called Graph Databases (GDB), based on a natural graph representation.

## References

SHOWING 1-10 OF 31 REFERENCES
Survey of graph database models
• Computer Science
CSUR
• 2008
The main objective of this survey is to present the work that has been conducted in the area of graph database modeling, concentrating on data structures, query languages, and integrity constraints.
Evaluating use of data flow systems for large graph analysis
• Computer Science
MTAGS '09
• 2009
It is found that a dataflow system can achieve orders of magnitude performance improvement over state-of-art database systems and serve as a viable scalable graph analysis engine.
Dex: high-performance exploration on large graphs for information retrieval
• Computer Science
CIKM '07
• 2007
DEX is proposed and evaluated, a high performance graph database querying system that allows for the integration of multiple data sources and makes graph querying possible in different flavors, including link analysis, social network analysis, pattern recognition and keyword search.
Expressive languages for path queries over graph-structured data
• Computer Science
PODS '10
• 2010
A class of extended CRPQs, called ECRPZs, are proposed, which add regular relations on tuples of paths, and allow path variables in the heads of queries, and study their properties.
Join processing in relational databases
• Computer Science
CSUR
• 1992
The different kinds of joins and the various implementation techniques are surveyed and they are classified based on how they partition tuples from different relations.
Graphs & Digraphs
• Mathematics
• 1986
Mapping Semantic Networks to Undirected Networks
The semantic network construct does not have any modeling functionality that is not possible with either a directed or undirected network representation, and two proofs of this idea will be presented.
A new path algebra for finding paths in graphs
• R. Manger
• Mathematics, Computer Science
26th International Conference on Information Technology Interfaces, 2004.
• 2004
A new path algebra is considered, which can be applied for finding one path between any pair of nodes in a graph, and it is proved that the proposed solution is correct and computationally efficient.