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WIREs Data Mining Knowl Discov
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Elastic stream processing in the Cloud

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Stream processing is a computing paradigm that has emerged from the necessity of handling high volumes of data in real time. In contrast to traditional databases, stream‐processing systems perform continuous queries and handle data on‐the‐fly. Today, a wide range of application areas relies on efficient pattern detection and queries over streams. The advent of Cloud computing fosters the development of elastic stream‐processing platforms, which are able to dynamically adapt based on different cost–benefit trade‐offs. This article provides an overview of the historical evolution and the key concepts of stream processing, with special focus on adaptivity and Cloud‐based elasticity. This article is categorized under: Application Areas > Data Mining Software Tools Technologies > Computer Architectures for Data Mining
Core artifacts and terminology.
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Different types of event stream query windows.
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Technologies > Computer Architectures for Data Mining
Application Areas > Data Mining Software Tools

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