api: YAML JSON TOON Database
version: 1.0.0
format: json
dataset:
  slug: cap-theorem
  title: CAP Theorem
  description: "The CAP theorem: a distributed data store can provide only two of three guarantees simultaneously."
  summary: "The CAP theorem's three guarantees (consistency, availability and partition tolerance) and what choosing CP or AP implies, extended with the PACELC refinement that describes the latency-versus-consistency trade-off when there is no partition."
  use_when[2]: You are explaining distributed-database trade-offs.,You need to check that a CAP claim about a product is stated correctly.
  caveats[2]: CAP applies to behavior during a partition. Saying a database 'is CP' or 'is AP' is a simplification that products often do not fit exactly.,"Consistency in CAP means linearizability, which is stricter than the 'C' in ACID."
  related[4]: acid-vs-base,nosql-databases-overview,newsql-distributed-sql,database-comparison
  category: Database Types
  category_slug: database-types
  tags: "database,cap,consistency,availability,partition"
  view_count: 0
  entry_count: 7
  fields[5]{section,field,type,example}:
    data,guarantee,string,Consistency
    data,description,string,Every read receives the most recent write or an…
    data,implication,string,All nodes see the same data at the same time.
    data,tradeoff,string,CP (Consistency + Partition Tolerance)
    data,examples,string,"HBase, MongoDB (in strict mode), Bigtable"
data[7]:
  - guarantee: Consistency
    description: Every read receives the most recent write or an error.
    implication: All nodes see the same data at the same time.
  - guarantee: Availability
    description: "Every request receives a response, without guarantee that it contains the most recent write."
    implication: Every node remains operational.
  - guarantee: Partition Tolerance
    description: The system continues to operate despite network partitions.
    implication: Messages between nodes may be lost.
  - tradeoff: CP (Consistency + Partition Tolerance)
    examples: "HBase, MongoDB (in strict mode), Bigtable"
    description: Sacrifices availability during partitions.
  - tradeoff: AP (Availability + Partition Tolerance)
    examples: "Cassandra, DynamoDB, CouchDB"
    description: Sacrifices strong consistency during partitions.
  - guarantee: PACELC (extension)
    description: "If there is a Partition, choose Availability or Consistency; Else, choose Latency or Consistency."
    implication: Captures that replication costs latency even when the network is healthy.
  - guarantee: CA (single node)
    description: "Consistency and availability without partition tolerance, achievable only when there is no network partition to tolerate."
    implication: Describes a single-node or tightly coupled system rather than a distributed one.