{
    "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": [
            "You are explaining distributed-database trade-offs.",
            "You need to check that a CAP claim about a product is stated correctly."
        ],
        "caveats": [
            "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": [
            "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": [
            {
                "section": "data",
                "field": "guarantee",
                "type": "string",
                "example": "Consistency"
            },
            {
                "section": "data",
                "field": "description",
                "type": "string",
                "example": "Every read receives the most recent write or an…"
            },
            {
                "section": "data",
                "field": "implication",
                "type": "string",
                "example": "All nodes see the same data at the same time."
            },
            {
                "section": "data",
                "field": "tradeoff",
                "type": "string",
                "example": "CP (Consistency + Partition Tolerance)"
            },
            {
                "section": "data",
                "field": "examples",
                "type": "string",
                "example": "HBase, MongoDB (in strict mode), Bigtable"
            }
        ]
    },
    "data": [
        {
            "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."
        }
    ]
}