Author Archives: admin

Simplifying and Scaling Data Discovery

By Raul Castro Fernandez, MIT CSAIL People who need access to data for their jobs are spending more and more time searching for data of interest to the task at hand. This is particularly true for data-driven companies, where the … Continue reading

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Rethinking Streaming: Correct State Matters!

by Nesime Tatbul, Intel Labs and MIT CSAIL; Kristin Tufte, Portland State University; and Stan Zdonik, Brown University Stream processing has largely been thought of as real-time analytics. Data enters the system as streams and analytic functions (aggregates) are computed on the … Continue reading

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ModelDB: A System for Managing Machine Learning Models

By Manasi Vartak, Harihar Subramanyam, Wei-En Lee, Srinidhi Viswanathan, Saadiyah Husnoo, Sam Madden and Matei Zaharia, MIT CSAIL Building real-world machine learning (ML) algorithms is an iterative process. A data scientist will build many 10s to 100s of models before arriving … Continue reading

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Larger-than-Memory Data Management on Modern Storage Hardware for In-Memory OLTP Database Systems

By Lin Ma, Carnegie Mellon University; Joy Arulraj, Carnegie Mellon University; Sam Zhao, Brown University; Andrew Pavlo, Carnegie Mellon University; Subramanya R. Dulloor, Intel Labs; Michael J. Giardino, Georgia Institute of Technology; Jeff Parkhurst, Jason L. Gardner, Kshitij Doshi, Intel Labs; and Col. Stanley Zdonik, Brown … Continue reading

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TicToc: Time Traveling Optimistic Concurrency Control

By Xiangyao Yu, MIT CSAIL; Andrew Pavlo, Carnegie Mellon; Daniel Sanchez and Srinivas Devadas, MIT CSAIL The TicToc algorithm enables scalable and high-performing concurrency control for future multi- and many-core systems. Large-scale, highly parallel transaction processing systems can be built with TicToc. We … Continue reading

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PolyPEG: A Proposal for Polystore Optimization

By Dylan Hutchison, Bill Howe, Dan Suciu, and Zachary Tatlock, University of Washington There has been a “cambrian explosion” of systems and languages for large-scale data analytics:  Postgres and H-Store accept SQL queries; Datomic and Myria accept Datalog; SciDB accepts … Continue reading

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Compiling Queries for High-Performance Computing

By Brandon Myers and Bill Howe, University of Washington High performance computing (HPC) is traditionally about compute, but its users have data management problems, too. In a recent paper, we demonstrated a promising technique for bringing ad hoc query processing into … Continue reading

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TileDB and GenomicsDB Now Available in Open Source

by Stavros Papadopoulos, Intel Parallel Computing Lab The ISTC for Big Data has recently released TileDB, a novel efficient data management system for scientific data, such as graphs, DNA sequences, matrices, maps, and imaging. We have also released an adaptation of TileDB … Continue reading

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ForeCache: Raising the Bar in Big Data Visual Exploration

By Leilani Battle, MIT CSAIL In many discussions with scientists across a variety of specialties, we have found that interactive visualizations are important tools for helping people make sense of massive amounts of data. In particular, interactive visualizations are critical … Continue reading

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Guaranteeing Query Runtimes for Analytics-as-a-Service

By Jennifer Ortiz and Magdalena Balazinska, University of Washington A variety of data analytics systems are available as cloud services today, including Amazon Elastic MapReduce (EMR), Redshift and Azure’s HDInsight. With these services, users have access to compute clusters that come … Continue reading

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