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Issues in data stream management
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Volume 32 ,  Issue 2  (June 2003) table of contents
Pages: 5 - 14  
Year of Publication: 2003
ISSN:0163-5808
Authors
Lukasz Golab  University of Waterloo, Canada
M. Tamer Özsu  University of Waterloo, Canada
Publisher
ACM  New York, NY, USA
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ABSTRACT

Traditional databases store sets of relatively static records with no pre-defined notion of time, unless timestamp attributes are explicitly added. While this model adequately represents commercial catalogues or repositories of personal information, many current and emerging applications require support for on-line analysis of rapidly changing data streams. Limitations of traditional DBMSs in supporting streaming applications have been recognized, prompting research to augment existing technologies and build new systems to manage streaming data. The purpose of this paper is to review recent work in data stream management systems, with an emphasis on application requirements, data models, continuous query languages, and query evaluation.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  90
Collaborative Colleagues:
Lukasz Golab: colleagues
M. Tamer Özsu: colleagues