Distributed data store: Difference between revisions

Revision as of 06:46, 13 September 2019

Revision as of 13:52, 18 September 2019

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| archive-url = https://web.archive.org/web/20170716092550/http://the-paper-trail.org/blog/bigtable-googles-distributed-data-store

| archive-date = 2017-07-16

| dead-url-status = yesdead

}}</ref> [[Amazon.com|Amazon]]'s [[Dynamo (storage system)|Dynamo]]<ref>{{cite web

| accessdate = 2011-04-05

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| quote = Dynamo: a highly available and scalable distributed data store

| url = http://www.cs.uwaterloo.ca/~kdaudjee/courses/cs848/slides/sarah1.pdf}}</ref>

and [[Azure Services Platform|Windows Azure Storage]].<ref>{{cite web|url=http://www.microsoft.com/windowsazure/features/storage/|title=Windows Azure Storage|author=|date=2011-09-16|work=|publisher=|accessdate=6 November 2011|deadurlurl-status=yesdead|archiveurl=https://web.archive.org/web/20111109002826/http://www.microsoft.com/windowsazure/features/storage/|archivedate=9 November 2011|df=}}</ref>

As the ability of arbitrary querying is not as important as the [[availability]], designers of distributed data stores have increased the latter at an expense of consistency. But the high-speed read/write access results in reduced consistency, as it is not possible to have both [[Consistency (database systems)|consistency]], availability, and partition tolerance of the network, as it has been proven by the [[CAP theorem]].