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Nesime Tatbul
Researcher at Intel
Publications - 126
Citations - 8419
Nesime Tatbul is an academic researcher from Intel. The author has contributed to research in topics: Stream processing & Query optimization. The author has an hindex of 33, co-authored 115 publications receiving 7753 citations. Previous affiliations of Nesime Tatbul include ETH Zurich & École Polytechnique.
Papers
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Proceedings Article
The Design of the Borealis Stream Processing Engine
Daniel J. Abadi,Yanif Ahmad,Magdalena Balazinska,Mitch Cherniack,Jeong-Hyon Hwang,Wolfgang Lindner,Anurag S. Maskey,Alexander Rasin,Esther Ryvkina,Nesime Tatbul,Ying Xing,Stan Zdonik +11 more
TL;DR: This paper outlines the basic design and functionality of Borealis, and presents a highly flexible and scalable QoS-based optimization model that operates across server and sensor networks and a new fault-tolerance model with flexible consistency-availability trade-offs.
Journal ArticleDOI
Aurora: a new model and architecture for data stream management
Daniel J. Abadi,Don Carney,Uğur Çetintemel,Mitch Cherniack,Christian Convey,Sangdon Lee,Michael Stonebraker,Nesime Tatbul,Stan Zdonik +8 more
TL;DR: The basic processing model and architecture of Aurora, a new system to manage data streams for monitoring applications, are described and a stream-oriented set of operators are described.
Book ChapterDOI
Monitoring streams: a new class of data management applications
Don Carney,Uǧur Çetintemel,Mitch Cherniack,Christian Convey,Sangdon Lee,Greg Seidman,Michael Stonebraker,Nesime Tatbul,Stan Zdonik +8 more
TL;DR: This paper presents Aurora, a new DBMS that is currently under construction at Brandeis University, Brown University, and M.I.T. and describes the basic system architecture, a stream-oriented set of operators, optimization tactics, and support for real-time operation.
Book ChapterDOI
Load shedding in a data stream manager
TL;DR: This paper examines a technique for dynamically inserting and removing drop operators into query plans as required by the current load, and addresses the problems of determining when load shedding is needed, where in the query plan to insert drops, and how much of the load should be shed at that point in the plan.
Proceedings ArticleDOI
Aurora: a data stream management system
Daniel J. Abadi,Don Carney,Uğur Çetintemel,Mitch Cherniack,Christian Convey,C. Erwin,E.F. Galvez,M. Hatoun,Anurag S. Maskey,Alexander Rasin,A. Singer,Michael Stonebraker,Nesime Tatbul,Ying Xing,R. Yan,Stanley B. Zdonik +15 more
TL;DR: This work proposes to demonstrate the Aurora system with its development environment and runtime system, with several example monitoring applications developed in consultation with defense, financial, and natural science communities, and shows the effect of various system alternatives on various workloads.