XLDB (eXtremely Large DataBases) was a yearly conference about databases, data management and analytics held from 2007 to 2019. The definition of extremely large refers to data sets that are too big in terms of volume (too much), and/or velocity (too fast), and/or variety (too many places, too many formats) to be handled using conventional solutions. This conference dealt with the high-end of very large databases (VLDB). It was conceived and chaired by Jacek Becla.
History
In October 2007, data experts gathered at SLAC National Accelerator Lab for the First Workshop on Extremely Large Databases. As a result, the XLDB research community was formed to meet the rapidly growing demands of the largest data systems. In addition to the original invitational workshop, an open conference, tutorials, and annual satellite events on different continents were added. The main event, held annually at Stanford University gathers over 300 attendees. XLDB is one of the data systems events catering to both academic and industry communities. For 2009, the workshop was co-located with VLDB 2009 in France to reach out to non-US research communities. XLDB 2019 followed Stanford's Conference on Systems and Machine Learning (SysML).
Goals
The main goals of this community include:
Identify trends, commonalities and major roadblocks related to building extremely large databases Bridge the gap between users trying to build extremely large databases and database solution providers worldwide Facilitate development and growth of practical technologies for extremely large data stores
XLDB Community As of 2013, the community consisted of over one thousand members including: Scientists who develop, use, or plan to develop or use XLDB for their research, from laboratories. Commercial users of XLDB. Providers of database products, including commercial vendors and representatives from open source database communities. Academic database researchers.
XLDB Conferences, Workshops and Tutorials The community met annually at Stanford University through 2019. Occasional satellite events were held in Asia and Europe.
A detailed report or videos was produced after each workshop.
Year Place Link Report Comments 2019 Stanford 12th XLDB Conference 2018 Stanford 11th XLDB Conference 2017 Clermont-Ferrand 10th XLDB Conference 2016 Stanford 9th XLDB Conference 2015 Stanford 8th XLDB Conference 2014 Observatório Nacional, Rio de Janeiro Satellite XLDB Workshop in South America 2014 Stony_Brook_University XLDB-Healthcare Workshop 2013 Stanford 7th XLDB Conference 2013 CERN, Geneva/Switzerland Satellite XLDB Workshop in Europe 2012 Stanford 6th XLDB Conference, Workshop & Tutorials 2012 Beijing, China Satellite XLDB Conference in Asia 2011 SLAC 5th XLDB Conference and Workshop 2011 Edinburgh, UK not available Satellite XLDB Workshop in Europe 2010 SLAC 4th XLDB Conference and Workshop 2009 Lyon, France 3rd XLDB Workshop 2008 SLAC 2nd XLDB Workshop 2007 SLAC 1st XLDB Workshop
Tangible results
XLDB events led to initiating an effort to build a new open source, science database called SciDB.
The XLDB organizers started defining a science benchmark for scientific data management systems called SS-DB.
At the XLDB organizers announced that two major databases that support arrays as first-class objects (MonetDB SciQL and SciDB) have formed a working group in conjunction with XLDB. This working group is proposing a common syntax (provisionally named “ArrayQL”) for manipulating arrays, including array creation and query.
See also
References
Further reading Pavlo A., Paulson E., Rasin A., Abadi D. J., Dewitt D. J., Madden S., and Stonebraker M., A Comparison of Approaches to Large-Scale Data Analysis, Proceedings of the 2009 ACM SIGMOD, https://web.archive.org/web/20090611174944/http://database.cs.brown.edu/sigmod09/benchmarks-sigmod09.pdf
Becla, J., & Wang, D. L. 2005, Lessons Learned from Managing a Petabyte, downloaded from https://web.archive.org/web/20110604223735/http://www.slac.stanford.edu/pubs/slacpubs/10750/slac-pub-10963.pdf on 2007-11-25.
Duellmann, D. 1999, Petabyte Databases, ACM SIGMOD Record, vol. 28, p. 506, https://web.archive.org/web/20071012015357/http://www.sigmod.org/sigmod/record/issues/9906/index.html#TutorialSessions. Hanushevsky, A., & Nowak, M. 1999, Pursuit of a Scalable High Performance Multi-Petabyte Database, 16th IEEE Symposium on Mass Storage Systems, pp. 169–175, http://citeseer.ist.psu.edu/217883.html. Shiers, J., Building Very Large, Distributed Object Databases, downloaded from https://web.archive.org/web/20070915101842/http://wwwasd.web.cern.ch/wwwasd/cernlib/rd45/papers/dbprog.html on 2007-11-25.
External links Official website