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 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.

In peer network data stores, the user can usually reciprocate and allow other users to use their computer as a storage node as well. Information may or may not be accessible to other users depending on the design of the network.

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