CAP Theorem on Distributed Databases :
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The CAP theorem, also known as Brewer’s theorem, is a fundamental concept in the field of distributed databases. It was formulated by computer scientist Eric Brewer in 2000.
The theorem states that in a distributed system, it is impossible to simultaneously achieve all three of the following guarantees:
Consistency ©: All nodes in the distributed system see the same data at the same time. In other words, a write operation on one node is immediately visible to all other nodes.
Availability (A): Every request to the system receives a response, without guarantee that it contains the most recent version of the information. This means that even if some nodes fail or are slow to respond, the system as a whole continues to provide responses.
Partition tolerance (P): The system continues to operate despite network partitions, meaning that messages between nodes may be delayed or lost.
According to the CAP theorem, a distributed system can prioritize at most two out of the three guarantees.
For example:
A system that prioritizes consistency and partition tolerance may sacrifice availability during network partitions.
A system that prioritizes availability and partition tolerance may sacrifice consistency, allowing nodes to return potentially stale or divergent data.
It’s important to note that the CAP theorem doesn’t imply that distributed systems must completely sacrifice one of these guarantees;
rather, it highlights the trade-offs that must be made in the face of network partitions.
Different distributed databases and systems make different choices based on their specific use cases and requirements.
For example:
CP systems (Consistency and Partition tolerance): Examples include traditional relational databases like PostgreSQL or systems like HBase.
AP systems (Availability and Partition tolerance): Examples include NoSQL databases like Couchbase or Cassandra.
CA systems (Consistency and Availability): In some scenarios, especially in smaller, more controlled environments, systems may prioritize consistency and availability over partition tolerance.
Understanding the CAP theorem helps architects and developers make informed decisions when designing and selecting distributed systems based on the specific needs and constraints of their applications.
