Authors:
Prasoon Dadhich
1
;
Andrey Sadovykh
1
;
Alessandra Bagnato
1
;
Michal Kepka
2
;
Ondřej Kaas
2
and
Karel Charvát
3
Affiliations:
1
Softeam Group, Paris and France
;
2
University of West Bohemia, Plze and Czech Republic
;
3
Lesprojekt-sluby Ltd., Martinov and Czech Republic
Keyword(s):
NoSQL, Performance Testing, Modeling, Data Migration, Benchmarking, Sensor-based Database, Cloud Computing, Virtualization, Scaling, Data Architecture and Analysis.
Related
Ontology
Subjects/Areas/Topics:
Architectural Concepts
;
Artificial Intelligence
;
Business Analytics
;
Data Analytics
;
Data Engineering
;
Data Management and Quality
;
Data Modeling and Visualization
;
Data Structures and Data Management Algorithms
;
Database Architecture and Performance
;
Databases and Data Security
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Large Scale Databases
;
Management of Sensor Data
;
Modeling and Managing Large Data Systems
;
Nosql Databases
;
Open Data
;
Open Source Databases
;
Organizational Concepts and Best Practices
;
Query Processing and Optimization
;
Symbolic Systems
Abstract:
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 solve 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 e
xisting 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.
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