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http://dx.doi.org/10.11108/kagis.2022.25.4.163

A Study on Effective Real Estate Big Data Management Method Using Graph Database Model  

Ju-Young, KIM (Department of Civil and Environmental Engineering, Seoul National University)
Hyun-Jung, KIM (School of Creative Convergence Education, Handong Global University)
Ki-Yun, YU (Department of Civil and Environmental Engineering, Seoul National University)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.25, no.4, 2022 , pp. 163-180 More about this Journal
Abstract
Real estate data can be big data. Because the amount of real estate data is growing rapidly and real estate data interacts with various fields such as the economy, law, and crowd psychology, yet is structured with complex data layers. The existing Relational Database tends to show difficulty in handling various relationships for managing real estate big data, because it has a fixed schema and is only vertically extendable. In order to improve such limitations, this study constructs the real estate data in a Graph Database and verifies its usefulness. For the research method, we modeled various real estate data on MySQL, one of the most widely used Relational Databases, and Neo4j, one of the most widely used Graph Databases. Then, we collected real estate questions used in real life and selected 9 different questions to compare the query times on each Database. As a result, Neo4j showed constant performance even in queries with multiple JOIN statements with inferences to various relationships, whereas MySQL showed a rapid increase in its performance. According to this result, we have found out that a Graph Database such as Neo4j is more efficient for real estate big data with various relationships. We expect to use the real estate Graph Database in predicting real estate price factors and inquiring AI speakers for real estate.
Keywords
Graph Database; Real Estate Big Data; Relational Database; Comparing Query Execution Time;
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Times Cited By KSCI : 1  (Citation Analysis)
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