Application of Graph Model in Smart Campus Data Center
In response to the problems of inconsistent data sources, low data quality and large data scale in the smart campus data platform, a graph modeling approach has been introduced. Although the data management and operation of mainstream structured database modeling methods are more reliable and mature, ensuring data integrity and consistency, their performance in querying diverse and complex data is poor. Unlike structured database modeling methods, graph models focus on the connections between data rather than the data itself, thus possessing the ability to easily handle complex, multi-level, and unstructured data. The application of the two modeling methods in the smart campus data center is studied and analyzed, and the query performance of the two methods is compared through experiments. The experimental results show that compared with the traditional relational modeling, the graph model can query and traverse the data faster and has better query efficiency when the data classification is complex and multiple classification join queries are often required. It solves the problem of poor query performance of smart campus data.
万方数据
维普
