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CAP Theorem y NoSQL Referencia

Referencia para el CAP theorem, NoSQL datos models, y consistency-availability tradeoffs.

CAP Theorem

The CAP theorem states distributed systems can provide at most two of: Consistency (all reads see latest write), Availability (every request gets a response), Partition tolerance (system works despite network partitions). Since partitions can happen, the real choice is CP (consistency + partition tolerance) or AP (availability + partition tolerance). CP systems (HBase, MongoDB strong) reject requests during partitions. AP systems (Cassandra, DynamoDB) may return stale data. Modern systems offer tunable consistency levels within these categories.

Consistency
Latest write visible
CP systems
Availability
Always responds
AP systems
Partition
Network splits
unavoidable

NoSQL Data Models

Key-value stores (Redis, DynamoDB) map keys to opaque values, simplest model. Document stores (MongoDB, CouchDB) store JSON-like documents with flexible schemas. Column-family (Cassandra, HBase) store data in column groups, efficient for wide/sparse data. Graph databases (Neo4j) store nodes and relationships, optimized for traversal. Time-series (InfluxDB, TimescaleDB) optimize for timestamped data. Search (Elasticsearch) optimize for full-text search. Each model fits specific use cases; polyglot persistence uses multiple stores.

key-value
Redis, DynamoDB
simplest
document
MongoDB, CouchDB
flexible schema
graph
Neo4j
relationship traversal

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