Paxos and Raft are Consensus Algorithms:A Comparison and Overview
barterauthorPaxos and Raft: A Comparison and Overview
In the world of distributed systems, consensus algorithms play a crucial role in ensuring the integrity and synchronization of data among separate nodes. Two of the most well-known consensus algorithms are Paxos and Raft. Both algorithms aim to achieve consensus on a set of data among a group of independent nodes. However, they differ in their design principles and implementation. In this article, we will compare and overview these two popular consensus algorithms to help you better understand their nuances and applicability in various distributed systems.
Paxos Algorithm
Paxos algorithm was originally proposed by Leslie Paxon and Michael Sherwood in 1990. It is a multi-pivot consensus algorithm, meaning that it can handle multiple leaders and proposes a single consensus value. The key components of the Paxos algorithm are:
1. Acceptor: An node that receives proposals and casts votes on the proposal it received.
2. Proposer: An node that sends proposals to acceptors and votes on the proposals it sent.
3. Voter: An node that receives proposals and casts votes on the proposal it received.
Paxos algorithm goes through three rounds:
1. Round 1: The proposer selects a value and sends proposals to all acceptors. Each acceptor casts a vote for the proposer's proposal.
2. Round 2: The proposer collects all votes from round 1 and selects the proposal with the most votes. Then, the proposer sends the selected proposal to all acceptors.
3. Round 3: Each acceptor verifies the proposal sent by the proposer and casts a vote for the proposal. The proposer also casts a vote for the proposal. If the proposal receives a majority of votes, it is considered accepted.
Raft Algorithm
Raft is a single-pivot consensus algorithm, which means that it has a single leader that proposes a consensus value. The key components of the Raft algorithm are:
1. Leader: A node that receives log entries from other nodes and sends proposals to follow nodes.
2. Follow: A node that receives log entries from the leader and casts votes on the proposal it received.
3. Candidate: A node that takes over as the leader if the current leader loses the majority vote.
Raft algorithm goes through multiple rounds:
1. Election: A candidate node announces its candidacy by sending its identity and a configuration request to the leader and follow nodes.
2. Voting: The leader sends proposals to the follow nodes and the candidate node. Each follow node and candidate node casts a vote for the proposal it received.
3. Decision: The leader collects votes and selects the proposal with the most votes. Then, the leader sends the selected proposal to all follow nodes.
Comparison
Although Paxos and Raft are both consensus algorithms, they differ in their design principles and implementation. Here is a comparison of their key differences:
1. Paxos is a multi-pivot consensus algorithm, while Raft is a single-pivot algorithm. This means that Raft has a single leader, while Paxos can have multiple leaders.
2. Paxos requires more round operations than Raft, which can lead to more communication overhead. Raft has fewer rounds, making it more efficient in terms of communication and execution.
3. Paxos is more robust to network partitions, as it can continue to operate even with some nodes disconnected. Raft requires a majority of nodes to be connected to function properly.
4. Paxos is more complex to implement and understand, while Raft is more straightforward and easy to implement.
Paxos and Raft are both popular consensus algorithms used in distributed systems. While they differ in their design principles and implementation, they both aim to achieve consensus on a set of data among a group of independent nodes. Paxos is more robust to network partitions and can handle multiple leaders, while Raft is more efficient and easy to implement. Choosing the right consensus algorithm depends on the specific requirements of the distributed system, such as communication overhead, network topology, and system complexity.