MODELING AND STORING DATA IN GRAPH DATABASES

Abstract

This paper presents the study of graph databases and their application in the context of social networks. It describes a data model that represents users, communities, and the relationships between them as a graph, where nodes represent objects and edges represent their relationships. The data structure in graph databases is compared to relational databases, emphasizing the freedom and flexibility to create and modify relationships between nodes without strict restrictions. A method for storing graph data structures is discussed, including the possibility of storing them in SQL tables using JSON, and the use of specialized graph DBMSs such as Neo4j. The specifics of data storage in Neo4j are highlighted, including caching for improving read/write performance and optimizing graph traversal. The paper emphasizes the Cypher query language, which is specifically used in Neo4j to work with graph data. Example queries with explanations are provided, demonstrating the capabilities of the Cypher language for working with data in graph databases. The conclusion discusses the application areas of graph databases, including fraud detection and supply chain mapping, how graph databases provide flexible options for storing information, and highlights their wide range of applications in various fields.