Graph Database Based Knowledge Graph Storage and Query for Power Equipment Management

The knowledge graph is a graph-based data structure that mines the value of data from a large number of associations. Therefore, it is necessary to find a database that can support the expression, storage, and query of associated data as a way of storing knowledge graph. Different than the normally used relational database and RDF tabular storage, the graph database stores data in “vertex” and “edge” as basic storage units, which can realize distributed storage and parallel processing of massive data with complex associations. The graph database utilizes the characteristics of physical “pointing” between nodes to provide “no index” association operations for adjacent nodes and has technical advantages in applications of network-structured data. This paper proposes a knowledge graph storage and query method based on the graph database, and compares the storage and query performance between the general storage format of RDF and graph database based on a constructed power equipment management knowledge graph.