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Compare Paxos and Raft

Last updated: Mar 29, 2026

Quick Overview

This question evaluates understanding of distributed consensus protocols, replicated logs, linearizability, fault tolerance, and operational concerns such as leader election, quorum semantics, log replication, membership changes, and failure recovery.

  • hard
  • Uber
  • System Design
  • Software Engineer

Compare Paxos and Raft

Company: Uber

Role: Software Engineer

Category: System Design

Difficulty: hard

Interview Round: Onsite

Explain how Paxos and Raft achieve consensus over a replicated log. Compare leader election, quorum requirements, log replication, membership changes, and behavior under partitions. Walk through failure scenarios (leader crash, message delays, disk loss) and recovery. Given goals of operational simplicity and debuggability, choose one for a new service and justify the trade-offs.

Quick Answer: This question evaluates understanding of distributed consensus protocols, replicated logs, linearizability, fault tolerance, and operational concerns such as leader election, quorum semantics, log replication, membership changes, and failure recovery.

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|Home/System Design/Uber

Compare Paxos and Raft

Uber logo
Uber
Sep 6, 2025, 12:00 AM
hardSoftware EngineerOnsiteSystem Design
15
0

Consensus over a Replicated Log: Paxos vs. Raft

Context

You are designing a fault-tolerant replicated log to back a stateful service (e.g., a key-value store). The system must be linearizable, tolerate crash-recovery failures and network partitions, and run on 2f+1 nodes to survive up to f failures.

Tasks

  1. Explain how Paxos (specifically Multi-Paxos) and Raft achieve consensus over a replicated log.
  2. Compare the two across:
    • Leader election
    • Quorum requirements
    • Log replication mechanics
    • Membership changes (cluster reconfiguration)
    • Behavior under network partitions
  3. Walk through failure scenarios and recovery:
    • Leader crash
    • Message delays/reordering
    • Disk loss
  4. Given goals of operational simplicity and debuggability, choose one for a new service and justify the trade-offs.

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