{"title":"Enhancing query performance of library information systems using NoSQL DBMS: Case study on library information systems of Universitas Indonesia","authors":"Herrnansyah, Y. Ruldeviyani, R. F. Aji","doi":"10.1109/IWBIS.2016.7872887","DOIUrl":null,"url":null,"abstract":"Library Automation and Digital Archive (Lontar) is a liblary information system developed by Universitas Indonesia and used by its main library. Rapid increase of library collections will soon make query performance of current SQL DBMS, which is MySQL, not fast enough to satisfy users and need to be complemented by NoSQL database, an emerging technology that specially developed for managing big data. The goal of this research is to implement and analyze the usage of NoSQL database to improve the query performance of Lontar. MongoDB is selected as NoSQL DBMS and the result shows that MongoDB is signficantly faster than MySQL.","PeriodicalId":193821,"journal":{"name":"2016 International Workshop on Big Data and Information Security (IWBIS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Workshop on Big Data and Information Security (IWBIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWBIS.2016.7872887","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Library Automation and Digital Archive (Lontar) is a liblary information system developed by Universitas Indonesia and used by its main library. Rapid increase of library collections will soon make query performance of current SQL DBMS, which is MySQL, not fast enough to satisfy users and need to be complemented by NoSQL database, an emerging technology that specially developed for managing big data. The goal of this research is to implement and analyze the usage of NoSQL database to improve the query performance of Lontar. MongoDB is selected as NoSQL DBMS and the result shows that MongoDB is signficantly faster than MySQL.