PipeGen: A Data Pipe Generator for Hybrid Analytics

By Brandon Haynes, Alvin Cheung, and Magdalena Balazinska, University of Washington As the number of big data management systems continues to grow, users increasingly seek to leverage multiple systems in the context of a single data analysis task. A critical challenge … Continue reading

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Interactive Search and Exploration over Large Multidimensional Data

by Alexander Kalinin, Ugur Cetintemel and Stan Zdonik of Brown University In the Big Data era, professionals across scientific areas need efficient, interactive ad-hoc data analysis. Ideally, they need generic and reusable systems tools for interactive search, exploration and mining … Continue reading

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Genomics Data, Analytics and the Future of Climate Change

By Vijay Gadepally, MIT CSAIL, in collaboration with the Chisholm Laboratory at MIT Meet Prochlorococcus marinus, a marine cyanobacterium that’s intricately linked to the global carbon cycle, widely present in seawater, and possibly holds secrets to future climate change. These … Continue reading

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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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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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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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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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Decibel: Dataset Branching for Collaborative Data Management

by Michael Maddox, MIT CSAIL, and Aaron J. Elmore, University of Chicago* In Big Data’s wake has come demand for tools to curate, manage and analyze shared datasets collaboratively. For instance, consider researchers in a social media company concurrently working … Continue reading

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