XLDB (eXtremely Large DataBases) is a yearly conference about
database
In computing, a database is an organized collection of data stored and accessed electronically. Small databases can be stored on a file system, while large databases are hosted on computer clusters or cloud storage. The design of databases s ...
s,
data management and
analytics. 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 deals with the high-end of
very large databases (VLDB). It was conceived and it is chaired by Jacek Becla.
History
In October 2007, data experts gathered at
SLAC National Accelerator Lab for th
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 above 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 meets annually at
Stanford University where the main event is held each Spring. Those who live too far from California to attend have the opportunity to attend occasional satellite events either in
Asia
Asia (, ) is one of the world's most notable geographical regions, which is either considered a continent in its own right or a subcontinent of Eurasia, which shares the continental landmass of Afro-Eurasia with Africa. Asia covers an are ...
or
Europe
Europe is a large peninsula conventionally considered a continent in its own right because of its great physical size and the weight of its history and traditions. Europe is also considered a subcontinent of Eurasia and it is located entirel ...
.
A detailed report or videos are produced after each workshop.
Tangible results
XLDB events led to initiating an effort to build a new open source, science database calle
SciDB
The XLDB organizers started defining
science benchmarkfor scientific data management systems called SS-DB.
A
XLDB 2012the XLDB organizers announced that two major databases that support arrays as
first-class objects (
MonetDB
MonetDB is an open-source column-oriented relational database management system (RDBMS) originally developed at the Centrum Wiskunde & Informatica (CWI) in the Netherlands.
It is designed to provide high performance on complex queries against l ...
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
*
International Conference on Very Large Data Bases
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* {{YouTube, u=XLDBConf, XLDBConf
Computer science conferences
Types of databases
Data management