AxomDB: A Distributed and Scalable In-memory Database System

Abstract

Memory (RAM) sizes are increasing day by day with cheaper costs due to emerging technologies, and it will continue to increase with a more affordable price. Therefore, in-memory database (IMDB) system exists as suitable choice for databases due to the high demands for the high-speed distributed database system. Moreover, with growing demand for real-time analytics on big data, requirement of distributed in-memory database systems is growing. Although they may sound trouble-free, in-memory databases bring some issues, making it hard to gain widespread usage. We propose a novel and intrinsic in-memory database system called AxomDB. This paper presents an efficient distributed in-memory database with Online Analytical Processing (OLAP) and Online Transactional Processing (OLTP) query processing capability in simultaneous manner, thus eliminating the need for a data warehouse or batch processing of big-data for analytical purposes. Also, we demonstrate an IMDB system with minimal use of secondary storage devices to ensure data persistence.