S4STRD: A Scalable in Memory Storage System for Spatio-temporal Real-Time Data

The popularity of applications that use spatio-temporal data in real-time has brought about the need for efficient storage systems. There exist different systems for storing data such as the traditional relational database management systems, NoSQL databases, RAM-based, and Hadoop/MapReduce based systems. However, due to the special characteristics of spatio-temporal data used in real-time applications, these available systems do not well match their performance requirements. This paper introduces a distributed RAM-based storage system that works in combination with an NoSQL database to provide better performance for real-time applications that uses huge volume of spatio-temporal data. Experiment results show that the proposed system gives better performance than disk-based NoSQL databases, and scales well when the volume of data is increased.