Stanford: Stream data manager

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In applications such as network monitoring, telecommunications data
management, web personalization, manufacturing, sensor networks, and
others, data takes the form of continuous data streams rather than
finite stored data sets, and clients require long-running continuous
queries as opposed to one-time queries. Traditional database systems
and data processing algorithms are ill-equipped to handle complex and
numerous continuous queries over data streams, and many aspects of
data management and processing need to be reconsidered in their
presence. In the STREAM project, we are reinvestigating data
management and query processing in the presence of multiple,
continuous, rapid, time-varying data streams. We are attacking
problems ranging from basic theory results to algorithms to
implementing a comprehensive prototype data stream management system.

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