International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 181 - Number 34 |
Year of Publication: 2018 |
Authors: Finna Suroso, Galih Hendro Martono |
10.5120/ijca2018918251 |
Finna Suroso, Galih Hendro Martono . A Brief Study of Comparison between Three Document Databases. International Journal of Computer Applications. 181, 34 ( Dec 2018), 24-29. DOI=10.5120/ijca2018918251
The development of data and volume has increased with the presence of the internet that is able to process and store data in the form of text, images, and videos. The emergence of big data provides a solution for companies to analyze data in real time. One of the most important points in big data is handling large data and volumes with the database. Conventional database concepts with Relational Database Management System (RDBM) models are unable to deal with these problems because they are less flexible in varying data handling. No SQL is a database used to solve problems from Big Data. There are four types of No SQL, namely Key-Value database, Document Database, Column Family Database, and Graph Database. The difference between them is data handling and processing methods. The document database is the most widely used No SQL database because it’s flexibility, easy to use, and similarities with RDBMS. This paper conducts a literature review of document databases, namely Monggo DB, Couch DB, and Couch Base. These three databases are selected because the three of them are the most widely used database. This paper not only compares the three databases in general but also, based on CAP Theorem. The purpose of this paper is to provide an overview of the three databases. Hopefully, this paper not only can give an overview of a document database but also understanding of advantages and disadvantages of each database so in practice users can choose the most suitable database for their need.