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Senska - Towards an Enterprise Streaming Benchmark

机译:Senska - 走向企业流媒体基准

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摘要

In the light of growing data volumes and continuing digitization in fields such as Industry 4.0 or Internet of Things, data stream processing have gained popularity and importance. Especially enterprises can benefit from this development by augmenting their vital, core business data with up-to-date streaming information. Enriching this transactional data with detailed information from high-frequency data streams allows answering new analytical questions as well as improving current analyses, e.g., regarding predictive maintenance. Comparing such data stream processing architectures for use in an enterprise context, i.e., when combining streaming and business data, is currently a challenging task as there is no suitable benchmark. In this paper, we give an overview about performance benchmarks in the area of data stream processing. We highlight shortcomings of existing benchmarks and present the need for a new benchmark with a focus on an enterprise context. Furthermore, the ideas behind Senska, a new enterprise streaming benchmark that shall fill this gap, and its architecture are introduced.
机译:根据日益增长的数据卷和行业4.0或物联网等领域的持续数字化,数据流处理已经获得了普及和重要性。特别是企业可以通过以最新的流媒体信息增强他们的重要核心业务数据,从而受益于此发展。从高频数据流的详细信息丰富了这种交易数据,允许应答新的分析问题以及改善当前分析,例如,关于预测维护。比较这些数据流处理体系结构用于企业上下文中的使用,即,在结合流和业务数据时,是当前是一个具有挑战性的任务,因为没有合适的基准。在本文中,我们概述了关于数据流处理领域的性能基准。我们突出了现有基准的缺点,并展示了一个新的基准,重点关注企业背景。此外,介绍了Senska背后的想法,这是一个新的企业流媒体基准,应填补这种差距及其架构。

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