XLDB

In October 2007, data experts gathered at SLAC National Accelerator Lab for the [https://web.archive.org/web/20080417002612/http://www-conf.slac.stanford.edu/xldb07/ 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.{{Cite web|url=https://www.symmetrymagazine.org/breaking/2009/09/16/building-the-biggest-scientific-databases|title=Building the biggest scientific databases|website=symmetry magazine|language=en|access-date=2019-04-15}} XLDB 2019 followed Stanford's Conference on Systems and Machine Learning (SysML).{{Cite web|url=https://conf.slac.stanford.edu/xldb2019/|title=XLDB Extremely Large Databases 2019|website=XLDB Extremely Large Databases 2019|access-date=2019-04-15}}

The main goals of this community include:{{ cite web | url=http://www-conf.slac.stanford.edu/xldb09/docs/xldb09_welcomeTalk.ppt | year=2009 | last=Becla| first=Jacek | title=XLDB 3 Welcome | access-date=2009-08-29 }}

• 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

As of 2013, the community consisted of over one thousand members including:

1. Scientists who develop, use, or plan to develop or use XLDB for their research, from laboratories.
2. Commercial users of XLDB.
3. Providers of database products, including commercial vendors and representatives from open source database communities.
4. Academic database researchers.

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.

XLDB events led to initiating an effort to build a new open source, science database called [https://web.archive.org/web/20090220121225/http://scidb.org/ SciDB].{{ cite web | url=http://www.jstage.jst.go.jp/article/dsj/7/0/88/_pdf | year=2008 | last=Becla| first=Jacek | title=Report from the SciDB Workshop |access-date=2008-09-29}}{{dead link|date=July 2016 |bot=InternetArchiveBot |fix-attempted=yes }}

The XLDB organizers started defining a [http://www.xldb.org/science-benchmark/ science benchmark] for scientific data management systems called SS-DB.

At [https://archive.today/20130416124054/http://xldb.org/2012 XLDB 2012] 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.

• International Conference on Very Large Data Bases

{{reflist}}

• 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
• {{cite book |doi=10.1117/12.671721|chapter=Designing a multi-petabyte database for LSST|title=Observatory Operations: Strategies, Processes, and Systems|year=2006|editor1-last=Silva|editor1-first=David R|last1=Becla|first1=Jacek|last2=Hanushevsky|first2=Andrew|last3=Nikolaev|first3=Sergei|last4=Abdulla|first4=Ghaleb|last5=Szalay|first5=Alex|last6=Nieto-Santisteban|first6=Maria|last7=Thakar|first7=Ani|last8=Gray|first8=Jim|s2cid=3204824|volume=6270|pages=62700R|editor2-first=Rodger E|editor2-last=Doxsey |arxiv=cs/0604112 }}
• 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.
• {{cite journal |last1=Bell |first1=Gordon |last2=Gray |first2=Jim |last3=Szalay |first3=Alex |title=Petascale Computational Systems |year=2007 |bibcode=2007cs........1165B |arxiv=cs/0701165 }}
• 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.

• [https://www.xldb.org Official website]
• {{YouTube|u=XLDBConf| XLDBConf }}

Category:Computer science conferences

Category:Types of databases

Category:Data management