Combining Relational and NoSQL Database Systems for Processing Sensor Data in Disaster Management
In disaster and emergency management the integration of different kinds of sensor networks gains in importance and consequently more and more data becomes available. The upcoming NoSQL database systems are flexible and scalable data stores, but up to now lacking in connectivity to traditional data processing systems (data warehouses, business intelligence suites, etc.). Due to that in this work a combined relational and NoSQL data processing approach is proposed to reduce data volume and work load of the relational part and enable the integral solution to process huge amounts of data. In contrast to fully NoSQL-based data warehouse systems, this approach does not face compatibility and integrability issues.
The research leading to these results has received funding from the ERA-NET EraSME program under the Austrian grant agreement No. 836684, project “INDYCO - Integrated Dynamic Decision Support System Component for Disaster Management Systems” and has been supported by the COMET program of the Austrian Research Promotion Agency (FFG).
- 3.Chodorow, K., Dirolf, M.: MongoDB - The Definitive Guide: Powerful and Scalable Data Storage. O’Reilly, Sebastopol (2010)Google Scholar
- 4.He, M. T. Gudyka: Build a Metadata-Driven ETL Platform by Extending Microsoft SQL Server Integration Services. SQL Server Technical Article. -, (2008)Google Scholar
- 5.Krishnan, K.: Data Warehousing in the Age of Big Data. Morgan Kaufmann Publishers Inc., San Francisco (2013)Google Scholar
- 6.Parker, Z. et al.: Comparing NoSQL MongoDB to an SQL DB. Proceedings of the 51st ACM Southeast Conference. pp. 5:1–5:6 ACM, Savannah, Georgia (2013)Google Scholar
- 9.Veen, J.S., van der et al.: Sensor data storage performance: SQL or NoSQL, physical or virtual. In: Chang, R. (ed.) IEEE Cloud, pp. 431–438. IEEE (2012)Google Scholar
- 10.Ziebermayr, T. et al.: A proposal for the application of dynamic workflows in disaster management: a process model language customized for disaster management. In: Morvan, F. et al. (eds.) DEXA Workshops, pp. 284–288. IEEE Computer Society (2011)Google Scholar