The Design of the Borealis Stream Processing Engine

By Daniel J. Abadi, Yanif Ahmad, M. Balazinska, Ugur Çetintemel, Mitch Cherniack, Jeong-Hyon Hwang, Wolfgang Lindner, Anurag Maskey, A. Rasin, Esther Ryvkina and 3 more. Conference on Innovative Data Systems Research, 2005

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Citations in the corpus

Aurora: a new model and architecture for data stream management (2003, background): “, open windows, SQL update & read operators, support for XML feeds, continued focus on performance Core Aurora system frozen and becoming commercial Follow-on system, called Borealis [2], in the works Distributed stream-processing system built on core streamprocessing functionality from Aurora”
A Framework for Partitioning and Execution of Data Stream Applications in Mobile Cloud Computing (2012, background): “Other efforts [2] [10] [13] [7] [11] in facilitating large scale cloud applications do not fit well in the MCC applications because they do not provide a flexible and adaptive mechanism to schedule the computation across the client and clouds.”
Focus: Querying Large Video Datasets with Low Latency and Low Cost (2018, background): “, [1,18,22,25,31,32,61,66,86, 87, 95]) and specific to video stream analytics (e.”
Live Video Analytics at Scale with Approximation and Delay-Tolerance (2017, methodology): “We considered streaming databases with approximation [19] [37] [68] as a starting point for our solution.”
S4: Distributed Stream Computing Platform (2010, background): “There are various projects and commercial engines ([6], [7], [8], [9], [10]), but their use is still restricted to highly specialized applications.”
Network-Aware Operator Placement for Stream-Processing Systems (2006, methodology): “To test this claim, we extended Borealis [7], an existing distributed stream processing engine, with our SBON implementation.”
Distributed data stream processing and edge computing: A survey on resource elasticity and future directions (2017, unknown): “Borealis [53] further extends the query functionalities of Aurora and the processing capabilities of Medusa [51] by dynamically revising query results, enabling query”
Monitoring Distributed, Heterogeneous Data Streams: The Emergence of Safe Zones (2014, background): “For a few years now, processing and monitoring of distributed streams has been emerging as a major effort in data management, with dedicated systems being developed for the task [4].”