Daniel Abadi
Rakesh Agrawal
Michael J. Carey
Johannes Gehrke
Laura M. Haas
Alon Y. Halevy
Joseph M. Hellerstein
Yannis E. Ioannidis
Tova Milo
Dan Suciu
Michael Stonebraker
Jennifer Widom
Abstract
Every few years a group of database researchers meets to discuss the state of database research, its impact on practice, and important new directions. This report summarizes the discussion and conclusions of the eighth such meeting, held October 14- 15, 2013 in Irvine, California. It observes that Big Data has now become a defining challenge of our time, and that the database research community is uniquely positioned to address it, with enormous opportunities to make transformative impact. To do so, the report recommends significantly more attention to five research areas: scalable big/fast data infrastructures; coping with diversity in the data management landscape; end-to-end processing and understanding of data; cloud services; and managing the diverse roles of people in the data life cycle.
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- Rakesh Agrawal, Anastasia Ailamaki, Philip A. Bernstein, Eric A. Brewer, Michael J. Carey, Surajit Chaudhuri, AnHai Doan, Daniela Florescu, Michael J. Franklin, Hector Garcia-Molina, Johannes Gehrke, Le Gruenwald, Laura M. Haas, Alon Y. Halevy, Joseph M. Hellerstein, Yannis E. Ioannidis, Hank F. Korth, Donald Kossmann, Samuel Madden, Roger Magoulas, Beng Chin Ooi, Tim O'Reilly, Raghu Ramakrishnan, Sunita Sarawagi, Michael Stonebraker, Alexander S. Szalay, and Gerhard Weikum. "The Claremont Report on Database Research." Communications of the ACM, 52(6):56--65, 2009 Google ScholarDigital Library
Index Terms
- The Beckman Report on Database Research
Recommendations
The Beckman report on database research
Database researchers paint big data as a defining challenge. To make the most of the enormous opportunities at hand will require focusing on five research areas.
Database Research: Are We at a Crossroad? Reflection on NoSQL
NBIS '12: Proceedings of the 2012 15th International Conference on Network-Based Information SystemsThe demand to process large sets of data has increased in the last few years from both the scientific and business community. To serve this demand, a number of new databases have been introduced that are not based on relational models. This group of ...
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