Editing Distributed data store (section)

==Distributed databases==
[[Distributed database]]s are usually [[non-relational database]]s that enable a quick access to data over a large number of nodes. Some distributed databases expose rich query abilities while others are limited to a [[key-value store]] semantics. Examples of limited distributed databases are [[Google]]'s [[Bigtable]], which is much more than a [[distributed file system]] or a [[peer-to-peer network]],<ref>{{cite web
| access-date = 2011-04-05
| publisher = Paper Trail
| title = Bigtable: Google's Distributed Data Store
| quote = Although GFS provides Google with reliable, scalable distributed file storage, it does not provide any facility for structuring the data contained in the files beyond a hierarchical directory structure and meaningful file names. It’s well known that more expressive solutions are required for large data sets. Google’s terabytes upon terabytes of data that they retrieve from web crawlers, amongst many other sources, need organising, so that client applications can quickly perform lookups and updates at a finer granularity than the file level. [...] The very first thing you need to know about Bigtable is that it isn’t a relational database. This should come as no surprise: one persistent theme through all of these large scale distributed data store papers is that RDBMSs are hard to do with good performance. There is no hard, fixed schema in a Bigtable, no referential integrity between tables (so no foreign keys) and therefore little support for optimised joins.
| url = http://the-paper-trail.org/blog/?p=86
| archive-url = https://web.archive.org/web/20170716092550/http://the-paper-trail.org/blog/bigtable-googles-distributed-data-store
| archive-date = 2017-07-16
| url-status = dead
}}</ref> [[Amazon.com|Amazon]]'s [[Dynamo (storage system)|Dynamo]]<ref>{{cite web
| access-date = 2011-04-05
| author = Sarah Pidcock
| date = 2011-01-31
| page = 2/22
| publisher = WATERLOO – CHERITON SCHOOL OF COMPUTER SCIENCE
| title = Dynamo: Amazon's Highly Available Key-value Store
| 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|Microsoft Azure Storage]].<ref>{{cite web|url=http://www.microsoft.com/windowsazure/features/storage/|title=Windows Azure Storage|website=[[Microsoft]] |date=2011-09-16|access-date=6 November 2011|url-status=dead|archive-url=https://web.archive.org/web/20111109002826/http://www.microsoft.com/windowsazure/features/storage/|archive-date=9 November 2011}}</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 guarantee both [[Consistency (database systems)|consistency]] and availability on a partitioned network, as stated by the [[CAP theorem]].