A Disk Based Stream Oriented Approach For Storing Big Data
| Authors |
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| Publication date | 2013 |
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| 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 |
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| ISBN (electronic) |
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| 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 |
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| 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.
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| Document type | Conference contribution |
| Language | English |
| Published at | https://doi.org/10.1109/CTS.2013.6567204 |
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