CAP theory for NoSQL system

Introduction to CAP

• Consistency means that each client always has the same view of the data.
• Availability means that all clients can always read and write.
• Partition tolerance means that the system works well across physical network partitions.

Consistent, Available (CA) Systems

have trouble with partitions and typically deal with it with replication.

• Traditional RDBMSs like Postgres, MySQL, etc (relational)
• Vertica (column-oriented)
• Aster Data (relational)
• Greenplum (relational)

Consistent, Partition-Tolerant (CP) Systems

have trouble with availability while keeping data consistent across partitioned nodes.

• BigTable (column-oriented/tabular)
• Hypertable (column-oriented/tabular)
• HBase (column-oriented/tabular)
• MongoDB (document-oriented)
• Terrastore (document-oriented)
• Redis (key-value)
• Scalaris (key-value)
• MemcacheDB (key-value)
• Berkeley DB (key-value)

Available, Partition-Tolerant (AP) Systems

achieve “eventual consistency” through replication and verification.

• Dynamo (key-value)
• Voldemort (key-value)
• Tokyo Cabinet (key-value)
• KAI (key-value)
• Cassandra (column-oriented/tabular)
• CouchDB (document-oriented)
• SimpleDB (document-oriented)
• Riak (document-oriented)

Reference

• https://blog.nahurst.com/visual-guide-to-nosql-systems