~welcome back with another post…
CAP theorem is a mathematical theorem that describes how an application behaves in the event of network partitioning.
This is also called as Brewer’s Theorem since the CAP theorem is created by Eric Brewer in 1998.
CAP acronyms for,
P- Partition Tolerance
Let’s see what these 3 guarantees elaborate…
This is a guaranty which defines that, every read receives the most recent write; therefore, all the nodes in the network see the same data at the same time.
This states that, every request receives a response; but it would not guarantee whether the response is the most recent write.
This defines that, the system will continue to operate despite the number of messages last among network nodes. Simply, it means the system will continues to perform even if there is a network outage in the data center.
***CAP theorem states that, at most 2 of the 3 guarantees can be achieved for a database…
NOSQL cannot provide consistency and high availability together…
Let’s see what are the database systems that can provide which 2 of the 3 guarantees of CAP theorem…
- CA — Consistency & Availability : RDBMS
- CP — Consistency & Partition Tolerance : MongoDB, HBase, Redis, BigTable
- AP — Availability & Partition Tolerance: Dynamo, Cassandra, CouchDB, Voldemart
We just briefly learned what is CAP Theorem.
That’s it for now, and please press the clap button if you find this article helpful.