Using Graph Databases for Querying and Network Analysing

Ristevski, Blagoj Using Graph Databases for Querying and Network Analysing. In: IX International Conference on Applied Internet and Information Technologies AIIT 2019, 3-4 October, Zrenjanin, Serbia.

[img]
Preview
Text
AIIT2019_ProceedingsFinal_Using Graph Databases for Querying.pdf

Download (327kB) | Preview

Abstract

Huge amounts of data are generated and used on a daily basis. This has led to the new concepts: big data and hybrid databases that are becoming more popular and promising. Thus, there is a need of integrating and storing data from various heterogeneous data sources. With the growth of data size, NoSQL databases have outperformed traditional relational databases for analysis, access and querying on big data. Relational databases store data in multiple tables and they are not suitable to represent numerous kinds of complex relationships among entities, particularly in computer networks, biological and social networks. On the other hand, graph databases rely on graph structure and are able to handle complex relationships. These databases use nodes representing entities and edges representing relationships, to present and store data. Graph database are very suitable for storing and querying heavily interconnected data, especially for large-scale network data. In this paper, Neo4j database and Cypher query language are described, and their using for analysis, querying and effectively mining of biological network's data.

Item Type: Conference or Workshop Item (Paper)
Subjects: Scientific Fields (Frascati) > Natural sciences > Computer and information sciences
Scientific Fields (Frascati) > Engineering and Technology > Electrical engineering, electronic engineering,information engineering
Divisions: Faculty of Information and Communication Technologies
Depositing User: Mrs Natasha Tabakovska
Date Deposited: 20 Jan 2020 13:07
Last Modified: 20 Jan 2020 13:07
URI: http://eprints.uklo.edu.mk/id/eprint/2340

Actions (login required)

View Item View Item