A Disk Based Stream Oriented Approach For Storing Big Data

Authors
Publication date 2013
Host editors
  • W.W. Smari
  • G.C. Fox
Book title Proceedings of the 2013 International Conference on Collaboration Technologies and Systems
Book subtitle May 20-24, 2013, Sheraton San Diego Hotel & Marina, San Diego, California
ISBN
  • 9781467364034
ISBN (electronic)
  • 9781467364041
  • 9781467364027
Event First International Symposium on Big Data and Data Analytics in Collaboration (BDDAC 2013). Part of The 2013 International Conference on Collaboration Technologies and Systems (CTS 2013)
Pages (from-to) 56-64
Publisher Piscataway, NJ: IEEE
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract
This paper proposes an extension to the generally accepted definition of Big Data and from this extended definition proposes a specialized database design for storing high throughput data from low-latency sources. It discusses the challenges a financial company faces with regards to processing and storing data and how existing database technologies are unsuitable for this niche task. A prototype database called CakeDB is built using a stream oriented, disk based storage design and insert throughput tests are conducted to demonstrate how effectively such a design would handle high throughput data as per the use case.
Document type Conference contribution
Language English
Published at https://doi.org/10.1109/CTS.2013.6567204
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