| Document Date: 2014-07-14 11:58:10
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City Hangzhou / New York City / / Company BikeShare / Creative Commons / Parallel OLTP Systems / Twitter / Intel / Stanley Zdonik1 1 Brown University 2 Intel Labs / / Country China / / / Facility Portland State University / Store DBMS / BikeShare station / STORE SYSTEM OVERVIEW S-Store / Store Supported Benchmarks / Store Architecture In / / IndustryTerm transaction processing / analytical processing / stream processing systems / native stream processing extensions / push-based workflow processing / classic stream processing workloads / social media / transactional processing primitives / transactional processing / streaming systems / real-time computations / online advertising / database systems / incremental processing / stream processing applications / real time / inherent stream processing semantics / low-level storage management / streaming applications / in-memory processing / fault-tolerant processing / push-based processing / continuous processing / data-driven processing / transaction management / stream processing / main-memory transaction processing engine / native stream processing support / big data applications / / MarketIndex OLTP / / NaturalFeature Discretized Streams / / OperatingSystem Microsoft Windows / / Organization VLDB Endowment / Portland State University / Center for Big Data / Brown University / MIT / BikeShare Stations and Nearby Discounts A BikeShare / / Person Hong Quatch / / ProgrammingLanguage SQL / Java / / ProvinceOrState Aurora / / PublishedMedium The VLDB Journal / / TVShow Canadian Dreamboat / / Technology Java / GPS / ISP / DBMS / / URL http /
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S-Store: A Streaming NewSQL System for Big Velocity Applications Ugur Cetintemel1 , Jiang Du2 , Tim Kraska1 , Samuel Madden3 , David Maier4 , John Meehan1 , Andrew Pavlo5 , Michael Stonebraker3 , Erik Sutherland4 , Nesim