Sensor-based Database with SensLog: A Case Study of SQL to NoSQL Migration

Prasoon Dadhich, Andrey Sadovykh, Alessandra Bagnato, Michal Kepka, Ondřej Kaas, Karel Charvát
2018 Proceedings of the 7th International Conference on Data Science, Technology and Applications  
Sensors gained a significant role in the Internet of Things (IoT) applications in various industry sectors. The information retrieved from the sensors are generally stored in the database for post-processing and analysis. This sensor database could grow rapidly when the data is frequently collected by several sensors altogether. It is thus often required to scale databases as the volume of data increases dramatically. Cloud computing and new database technologies has become key technologies to
more » ... olve these problems. Traditionally relational SQL databases are widely used and have proved reliable over time. However, the scalability of SQL databases at large scale has always been an issue. With the ever-growing data volumes, various new database technologies have appeared which proposes performance and scalability gains under severe conditions. They have often named as NoSQL databases as opposed to SQL databases. One of the challenges that have arisen is knowing how and when to migrate existing relational databases to NoSQL databases for performance and scalability. In the current paper, we present a work in progress with the DataBio project for the SensLog application case study with some initial success. We will report on the ideas and the migration approach of SensLog platform and the performance benchmarking.
doi:10.5220/0006909202390244 dblp:conf/data/DadhichSBKKC18 fatcat:gw77x43lfffbjlehj7aw6d3ape