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  2. CAP theorem - Wikipedia

    en.wikipedia.org/wiki/CAP_theorem

    The PACELC theorem, introduced in 2010, [8] builds on CAP by stating that even in the absence of partitioning, there is another trade-off between latency and consistency. PACELC means, if partition (P) happens, the trade-off is between availability (A) and consistency (C); Else (E), the trade-off is between latency (L) and consistency (C).

  3. 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 ...

  4. 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 ...

  5. 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.

  6. Quorum (distributed computing) - Wikipedia

    en.wikipedia.org/wiki/Quorum_(distributed_computing)

    In a distributed database system, a transaction could execute its operations at multiple sites. Since atomicity requires every distributed transaction to be atomic, the transaction must have the same fate (commit or abort) at every site.

  7. PACELC theorem - Wikipedia

    en.wikipedia.org/wiki/PACELC_theorem

    The PACELC theorem was first described by Daniel Abadi from Yale University in 2010 in a blog post, [2] which he later clarified in a paper in 2012. [3] The purpose of PACELC is to address his thesis that "Ignoring the consistency/latency trade-off of replicated systems is a major oversight [in CAP], as it is present at all times during system operation, whereas CAP is only relevant in the ...

  8. Aerospike (database) - Wikipedia

    en.wikipedia.org/wiki/Aerospike_(database)

    Since version 4.0 (2018), Aerospike Database can be configured both as Available and Partition-tolerant (AP) or Consistent and Partition-tolerant (CP) under the CAP theorem. [37] [38] The client cluster-aware layer is used to track the cluster configuration in the database, and manages client direct communications to all the nodes in the ...

  9. ACID - Wikipedia

    en.wikipedia.org/wiki/ACID

    In computer science, ACID (atomicity, consistency, isolation, durability) is a set of properties of database transactions intended to guarantee data validity despite errors, power failures, and other mishaps.