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The Beckman Report on Database Research

By Daniel Abadi, Rakesh Agrawal, Anastasia Ailamaki, Magdalena Balazinska, Philip A. Bernstein, Michael J. Carey, Surajit Chaudhuri, Jeffrey Dean, AnHai Doan, Michael J. Franklin, Johannes Gehrke, Laura M. Haas, Alon Y. Halevy, Joseph M. Hellerstein, Yannis E. Ioannidis, H. V. Jagadish, Donald Kossmann, Samuel Madden, Sharad Mehrotra, Tova Milo, Jeffrey F. Naughton, Raghu Ramakrishnan, Volker Markl, Christopher Olston, Beng Chin Ooi, Christopher Ré, Dan Suciu, Michael Stonebraker, Todd Walter,

Communications of the ACM, Vol. 59 No. 2, Pages 92-99

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A group of database researchers meets periodically to discuss the state of the field and its key directions going forward. Past meetings were held in 1989,6 1990,11 1995,12 1996,10 1998,7 2003,1 and 2008.2 Continuing this tradition, 28 database researchers and two invited speakers met in October 2013 at the Beckman Center on the University of California-Irvine campus for two days of discussions. The meeting attendees represented a broad cross-section of interests, affiliations, seniority, and geography. Attendance was capped at 30 so the meeting would be as interactive as possible. This article summarizes the conclusions from that meeting; an extended report and participant presentations are available at http://beckman.cs.wisc.edu.

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Key Insights


The meeting participants quickly converged on big data as a defining challenge of our time. Big data arose due to the confluence of three major trends. First, it has become much cheaper to generate a wide variety of data, due to inexpensive storage, sensors, smart devices, social software, multiplayer games, and the Internet of Things, which connects homes, cars, appliances, and other devices. Second, it has become much cheaper to process large amounts of data, due to advances in multicore CPUs, solid state storage, inexpensive cloud computing, and open source software. Finally, data management has become democratized. The process of generating, processing, and consuming data is no longer just for database professionals. Decision makers, domain scientists, application users, journalists, crowd workers, and everyday consumers now routinely do it.


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