MOVING POINT DATA MANAGEMENT ON DOCUMENT ORIENTED NOSQL DATABASE

• Main Author: Isriyanto, Kharis
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/36944
• Institution: Institut Teknologi Bandung

The development of GPS technology leads to the development of mobile application that can use moving object data, particularly moving point. Mobile application can track user’s location and record all the movement of the user, creating a lot of movement data for each user. But until this final project is created, there is no DBMS (Database Management System) that can manage moving point, because of the difficulties to store, update, and do operation/query on moving point data, especially on classic relational database. There is a document-oriented NoSQL database that can handle complex data, semi-structured data, and more flexible compared to relational database. Document oriented NoSQL database will be used to manage moving point data. In this final project, the existing moving point data model, that is moving point as sequence of point, is mapped to document-oriented NoSQL data model in JSON format. ST-Hash index is implemented to group a nearby point in certain time, so spatio-temporal query speed can be accelerated. An API is built to handle moving point data, starting from creating, storing, indexing, and query moving object processing. Moving point data in JSON format can be saved by API and be processed by spatio-temporal query. API can be implemented well. But some obstacles were found. One of the obstacles is the processing of big data. The memory will run out and query cannot be executed. Performance evaluation is done between MongoDB and PostGreSQL. Generally query execution in MongoDB is faster than in PostGreSQL.