Modelling Metadata and Data from Censuses and Surveys with Graph Databases

Relational database users are switching to non-relational databases because non-relational databases are better able to handle dynamic data storage. One of the institutions that require dynamic data storage is Statistics Indonesia (BPS). Currently, data storage for census and survey activities at BP...

詳細記述

書誌詳細
出版年:Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
主要な著者: Alya Faradila, Lutfi Rahmatuti Maghfiroh
フォーマット: 論文
言語:英語
出版事項: Ikatan Ahli Informatika Indonesia 2023-09-01
主題:
オンライン・アクセス:http://jurnal.iaii.or.id/index.php/RESTI/article/view/5273
その他の書誌記述
要約:Relational database users are switching to non-relational databases because non-relational databases are better able to handle dynamic data storage. One of the institutions that require dynamic data storage is Statistics Indonesia (BPS). Currently, data storage for census and survey activities at BPS is done using a relational database, although there are metadata changes in each activity. Accommodating metadata changes in each activity requires one database, which creates problems when retrieving some raw data. There is an opportunity for convenience if the data collected is stored in a non-relational database, one of which is a graph database. This research discusses the modeling of metadata and data from censuses and surveys at BPS using a graph database. Then we implement the Neo4j DBMS and compare the proposed model with the relational model in the Microsoft SQL Server DBMS. Then, a comparison of the features and characteristics of each DBMS is done, and finally, performance testing is done with Apache JMeter. Modeling has been able to handle dynamic data structure changes, but Neo4j's performance is still lagging behind Microsoft SQL Server.
ISSN:2580-0760