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・ Distributed cognition
・ Distributed Common Ground System
・ Distributed Component Object Model
・ Distributed computing
・ Distributed Computing (journal)
・ Distributed Computing Environment
・ Distributed concurrency control
・ Distributed Concurrent Versions System
・ Distributed constraint optimization
・ Distributed control system
・ Distributed coordination function
・ Distributed creativity
・ Distributed data flow
・ Distributed Data Management Architecture
・ Distributed Data Protocol
Distributed data store
・ Distributed database
・ Distributed Database Consulting
・ Distributed denial-of-service attacks on root nameservers
・ Distributed design patterns
・ Distributed development
・ Distributed economy
・ Distributed element filter
・ Distributed element model
・ Distributed European Infrastructure for Supercomputing Applications
・ Distributed Event-Based Systems
・ Distributed feedback laser
・ Distributed file system (disambiguation)
・ Distributed File System (Microsoft)
・ Distributed file system for cloud


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Distributed data store : ウィキペディア英語版
Distributed data store

A distributed data store is a computer network where information is stored on more than one node, often in a replicated fashion. It is usually specifically used to refer to either a distributed database where users store information on a ''number of nodes'', or a computer network in which users store information on a ''number of peer network nodes''.
==Distributed databases==
Distributed databases are usually non-relational databases that make a quick access to data over a large number of nodes possible. 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, Amazon's Dynamo
and Windows Azure Storage.
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, availability, and partition tolerance of the network, as it has been proven by the CAP theorem.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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