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  2. CAP theorem - Wikipedia

    en.wikipedia.org/wiki/CAP_theorem

    Note that consistency as defined in the CAP theorem is quite different from the consistency guaranteed in ACID database transactions. [4] Availability Every request received by a non-failing node in the system must result in a response. This is the definition of availability in CAP theorem as defined by Gilbert and Lynch. [1]

  3. NoSQL - Wikipedia

    en.wikipedia.org/wiki/NoSQL

    Many NoSQL stores compromise consistency (in the sense of the CAP theorem) in favor of availability, partition tolerance, and speed. Barriers to the greater adoption of NoSQL stores include the use of low-level query languages (instead of SQL, for instance), lack of ability to perform ad hoc joins across tables, lack of standardized interfaces ...

  4. Consistency (database systems) - Wikipedia

    en.wikipedia.org/wiki/Consistency_(database_systems)

    The CAP theorem is based on three trade-offs, one of which is "atomic consistency" (shortened to "consistency" for the acronym), about which the authors note, "Discussing atomic consistency is somewhat different than talking about an ACID database, as database consistency refers to transactions, while atomic consistency refers only to a property of a single request/response operation sequence.

  5. Column (data store) - Wikipedia

    en.wikipedia.org/wiki/Column_(data_store)

    A column is used as a store for the value and has a timestamp that is used to differentiate the valid content from stale ones. According to the CAP theorem, distributed data stores cannot guarantee consistency, as availability and partition tolerance are more important issues. Therefore, the data store or the application programmer will use the ...

  6. PACELC theorem - Wikipedia

    en.wikipedia.org/wiki/PACELC_theorem

    The tradeoff between availability, consistency and latency, as described by the PACELC theorem. In database theory, the PACELC theorem is an extension to the CAP theorem.It states that in case of network partitioning (P) in a distributed computer system, one has to choose between availability (A) and consistency (C) (as per the CAP theorem), but else (E), even when the system is running ...

  7. Couchbase Server - Wikipedia

    en.wikipedia.org/wiki/Couchbase_Server

    Starting with the 4.0 release, the three services can be distributed to run on separate nodes of the cluster if needed. In the parlance of Eric Brewer's CAP theorem, Couchbase is normally a CP type system meaning it provides consistency and partition tolerance, or it can be set up as an AP system with multiple clusters.

  8. Distributed SQL - Wikipedia

    en.wikipedia.org/wiki/Distributed_SQL

    relational database front end structure – meaning data represented as tables with rows and columns similar to any other RDBMS; automatically sharded data storage; underlying key–value storage [7] [1] native SQL implementation; Following the CAP Theorem, distributed SQL databases are "CP" or consistent and partition-tolerant. Algorithmically ...

  9. Network partition - Wikipedia

    en.wikipedia.org/wiki/Network_partition

    The CAP theorem is based on three trade-offs: consistency, availability, and partition tolerance. Partition tolerance, in this context, means the ability of a data processing system to continue processing data even if a network partition causes communication errors between subsystems.