Stream-processing systems are designed to support an emerging class of applications that require sophisticated and timely processing of high-volume data streams, often originating...
Alex Rasin, Jeong-Hyon Hwang, Magdalena Balazinska...
Detecting bursts in data streams is an important and challenging task. Due to the complexity of this task, usually burst detection cannot be formulated using standard query operat...
Online Analytical Processing is a powerful framework for the analysis of organizational data. OLAP is often supported by a logical structure known as a data cube, a multidimension...
Frank K. H. A. Dehne, Todd Eavis, Andrew Rau-Chapl...
The past decade has seen a wealth of research on time series representations, because the manipulation, storage, and indexing of large volumes of raw time series data is impractic...
Themistoklis Palpanas, Michail Vlachos, Eamonn J. ...
Due to an increasing volume of XML data, it is considered prudent to store XML data on an industry-strength database system instead of relying on a domain specific application or...