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A Demonstration of the BigDAWG Polystore System

by A Elmore , J Duggan , Northwestern M Stonebraker , Mit M Balazinska , U Cetintemel Brown , V Gadepally , J Heer , B Howe , J Kepner
"... ABSTRACT This paper presents BigDAWG, a reference implementation of a new architecture for "Big Data" applications. Such applications not only call for large-scale analytics, but also for real-time streaming support, smaller analytics at interactive speeds, data visualization, and cross-s ..."
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ABSTRACT This paper presents BigDAWG, a reference implementation of a new architecture for "Big Data" applications. Such applications not only call for large-scale analytics, but also for real-time streaming support, smaller analytics at interactive speeds, data visualization, and cross-storage-system

Polystore Query Rewriting: The Challenges of Variety

by unknown authors
"... Numerous databases marketed as SQL-on-Hadoop, NewSQL [16] and NoSQL have emerged to catalyze Big Data applications. These databases generally support the 3Vs [7]. (i) Volume: amount of data (ii) Velocity: speed of data in and out (iii) Variety: semi-structured and het-erogeneous data. As a result of ..."
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Numerous databases marketed as SQL-on-Hadoop, NewSQL [16] and NoSQL have emerged to catalyze Big Data applications. These databases generally support the 3Vs [7]. (i) Volume: amount of data (ii) Velocity: speed of data in and out (iii) Variety: semi-structured and het-erogeneous data. As a result

Data Ingestion for the Connected World

by John Meehan , Cansu Aslantas , Stan Zdonik , Nesime Tatbul , Jiang Du
"... ABSTRACT In this paper, we argue that in many "Big Data" applications, getting data into the system correctly and at scale via traditional ETL (Extract, Transform, and Load) processes is a fundamental roadblock to being able to perform timely analytics or make real-time decisions. The bes ..."
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implementation of streaming ETL using a scalable messaging system (Apache Kafka), a transactional stream processing system (S-Store), and a distributed polystore (Intel's BigDAWG), as well as propose a new time-series database optimized to handle ingestion internally.

Intel

by A. Elmore, J. Duggan, M. Stonebraker, M. Balazinska, U. Cetintemel, V. Gadepally, J. Heer, B. Howe, J. Kepner, T. Kraska, S. Madden, D. Maier, T. Mattson, S. Papadopoulis, J. Parkhurst, N. Tatbul, M. Vartek, S. Zdonik
"... This paper presents BigDAWG, a reference implementation of a new architecture for “Big Data ” applications. Such applications not only call for large-scale analytics, but also for real-time stream-ing support, smaller analytics at interactive speeds, data visualiza-tion, and cross-storage-system que ..."
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This paper presents BigDAWG, a reference implementation of a new architecture for “Big Data ” applications. Such applications not only call for large-scale analytics, but also for real-time stream-ing support, smaller analytics at interactive speeds, data visualiza-tion, and cross-storage-system

Northwestern

by A. Elmore, J. Duggan, M. Stonebraker, M. Balazinska, U. Cetintemel, V. Gadepally, J. Heer, B. Howe, J. Kepner, T. Kraska, S. Madden, D. Maier, T. Mattson, J. Parkhurst, N. Tatbul, M. Vartak, S. Zdonik
"... This paper presents BigDAWG, a reference implementation of a new architecture for “Big Data ” applications. Such applications not only call for large-scale analytics, but also for real-time stream-ing support, smaller analytics at interactive speeds, data visualiza-tion, and cross-storage-system que ..."
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This paper presents BigDAWG, a reference implementation of a new architecture for “Big Data ” applications. Such applications not only call for large-scale analytics, but also for real-time stream-ing support, smaller analytics at interactive speeds, data visualiza-tion, and cross-storage-system
Results 1 - 5 of 5