Usage of CAP Theorem in Today's Distributed Storage Systems

CAP Theorem (Eric Brewer) states that a Distributed System can provide at most two of three properties -Consistency, Partition Tolerance, and Availability.

Partition Tolerance is a must in real world systems since machines fail all the time. Therefore, a distributed system has to pick either Availability or Consistency as the second property. Consistency means "always return the correct value" - eg:the latest written one. And availability is "always accept requests" - eg: read & write.
Picking one of these does not always mean loosing the other totally. If application favors from availability, eg: shoppping cart, it is better to prioritize availability and resolving consistency issues later (eventually consistent). On the other hand, if application requires consistency, eg: checkout or backend systems which doesn't require instant response to end user, better to prioritize consistency and give up availability.

Here are some examples:
- Amazon's Dynamo, LinkedIn's Project Voldemort and Facebook's Cassandra provide high availability, but eventual consistency.
- On the other side, Google's Bigtable provides strong consistency and gives up high availability. HyperTable and HBAse are using BigTable approach.