Efficient NoSQL Graph Database for Storage and Access of Health Data

Abstract

Graph data models are mostly used for storage and access of large, unstructured real-life data generated from real-life applications. The graph data model can be implemented by NoSQL graph databases. In this paper, eight well-known NoSQL graph databases are compared to study their properties. After rigorous review of different research works which are focused on different parametric measures of storage and access, only the best three NoSQL graph databases, Neo4j, OrientDB and ArangoDB, are chosen. The efficiency of these three graph databases is compared based on searching or traversing and querying operations on the databases for storage and access. A particular type of graph, i.e., disease-symptom graph database has been used for this purpose.