About: Causal consistency     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : owl:Thing, within Data Space : el.dbpedia.org associated with source document(s)

Causal consistency is one of the major memory consistency models. In concurrent programming, where concurrent processes are accessing a shared memory, a consistency model restricts which accesses are legal. This is useful for defining correct data structures in distributed shared memory or distributed transactions.

AttributesValues
rdfs:label
  • Causal consistency (en)
rdfs:comment
  • Causal consistency is one of the major memory consistency models. In concurrent programming, where concurrent processes are accessing a shared memory, a consistency model restricts which accesses are legal. This is useful for defining correct data structures in distributed shared memory or distributed transactions. (en)
sameAs
dbp:wikiPageUsesTemplate
Subject
Link from a Wikipage to an external page
prov:wasDerivedFrom
Wikipage page ID
page length (characters) of wiki page
Wikipage revision ID
Link from a Wikipage to another Wikipage
has abstract
  • Causal consistency is one of the major memory consistency models. In concurrent programming, where concurrent processes are accessing a shared memory, a consistency model restricts which accesses are legal. This is useful for defining correct data structures in distributed shared memory or distributed transactions. Causal Consistency is “Available under Partition”, meaning that a process can read and write the memory (memory is Available) even while there is no functioning network connection (network is Partitioned) between processes; it is an asynchronous model. Contrast to strong consistency models, such as sequential consistency or linearizability, which cannot be both safe and live under partition, and are slow to respond because they require synchronisation. Causal consistency was proposed in 1990s as a weaker consistency model for shared memory models. Causal consistency is closely related to the concept of Causal Broadcast in communication protocols. In these models, a distributed execution is represented as a partial order, based on Lamport's happened-before concept of potential causality. Causal consistency is a useful consistency model because it matches programmers' intuitions about time, is more available than strong consistency models, yet provides more useful guarantees than eventual consistency. For instance, in distributed databases, causal consistency supports the ordering of operations, in contrast to eventual consistency. Also, causal consistency helps with the development of abstract data types such as queues or counters. Since time and ordering are so fundamental to our intuition, it is hardto reason about a system that does not enforce causal consistency.However, many distributed databases lack this guarantee, even ones thatprovide serialisability.Spanner does guarantee causal consistency, but it also forces strong consistency, thus eschewing availability under partition.More available databases that ensure causal consistency include MongoDBand AntidoteDB. (en)
foaf:isPrimaryTopicOf
is Wikipage redirect of
is Link from a Wikipage to another Wikipage of
is foaf:primaryTopic of
Faceted Search & Find service v1.17_git151 as of Feb 20 2025


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Nov 11 2024, on Linux (x86_64-ubuntu_focal-linux-gnu), Single-Server Edition (72 GB total memory, 1 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2025 OpenLink Software