Authors:
Jaroslav Pokorný
1
;
Michal Valenta
2
and
Martin Troup
2
Affiliations:
1
Faculty of Mathematics and Physics, Charles University, Prague and Czech Republic
;
2
Faculty of Information Technology, Czech Technical University, Prague and Czech Republic
Keyword(s):
Graph Databases, Indexing Patterns, Graph Pattern, Graph Database Schema, Neo4j.
Related
Ontology
Subjects/Areas/Topics:
Data Engineering
;
Database Architecture and Performance
;
Databases and Data Security
;
Nosql Databases
Abstract:
Nowadays graphs have become very popular in domains like social media analytics, healthcare, natural sciences, BI, networking, graph-based bibliographic IR, etc. Graph databases (GDB) allow simple and rapid retrieval of complex graph structures that are difficult to model in traditional IS based on a relational DBMS. GDB are designed to exploit relationships in data, which means they can uncover patterns difficult to detect using traditional methods. We introduce a new method for indexing graph patterns within a GDB modelled as a labelled property graph. The index is organized in a tree structure and stored in the same database where the database graph. The method is analysed and implemented for Neo4j GDB engine. It enables to create, use and update indexes that are used to speed-up the process of matching graph patterns. The paper provides a comparison between queries with and without using indexes.