The PACELC theorem is an extension of the CAP theorem, which addresses the trade-offs in distributed systems. While the CAP theorem states that a distributed system can only guarantee two out of three properties—Consistency (C), Availability (A), and Partition Tolerance (P)—the PACELC theorem adds another dimension to this by considering the system's behavior in the absence of network partitions.
Explanation of PACELC Theorem
The PACELC theorem, proposed by Daniel Abadi, states that in the case of a network partition (P), a distributed system must choose between Availability (A) and Consistency (C), similar to the CAP theorem. However, it goes further by addressing the trade-offs that exist even when the system is running normally without partitions (Else, E). In such cases, the system must choose between Latency (L) and Consistency (C).
In summary, the PACELC theorem can be broken down as follows:
P (Partitioned): If there is a network partition, the system must choose between Availability (A) and Consistency (C).
EL (Else): If there is no network partition, the system must choose between Latency (L) and Consistency (C).
Key Points
Partition Tolerance (P): This is a given in distributed systems, as network partitions are inevitable.
Availability (A) vs. Consistency (C): During a partition, the system must decide whether to remain available (respond to all requests) or to ensure consistency (all nodes see the same data).
Latency (L) vs. Consistency (C): When there is no partition, the system must decide whether to prioritize low latency (quick responses) or consistency (ensuring all nodes have the same data).
Examples
PA/EL Systems: Systems like DynamoDB and Cassandra prioritize Availability during partitions and Latency during normal operations.
PC/EC Systems: Systems like Bigtable and HBase prioritize Consistency both during partitions and normal operation...
