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Raft

163 articles · Page 2 of 2
JD Cloud Developers
JD Cloud Developers
Dec 24, 2020 · Cloud Native

How JD Cloud’s JCQ Redefines Cloud‑Native Messaging with Compute‑Storage Separation

JCQ, JD Cloud’s self‑developed cloud‑native message queue, evolved from a monolithic 1.0 version to a 3.0 architecture that separates compute and storage, introduces multi‑Raft scaling, dynamic resource allocation, and high‑availability features, offering flexible, low‑maintenance messaging for high‑concurrency workloads.

Message QueueRaftcloud-native
0 likes · 10 min read
How JD Cloud’s JCQ Redefines Cloud‑Native Messaging with Compute‑Storage Separation
Architecture Digest
Architecture Digest
Nov 26, 2020 · Fundamentals

Two-Phase Commit, Paxos, and Raft: Core Concepts and Workflows

This article explains the principles and workflows of Two‑Phase Commit, Paxos, and Raft, detailing their roles, phases, failure handling, and how they achieve distributed consensus in fault‑tolerant systems, including the coordinator‑participant model, proposal numbering, leader election, heartbeat mechanisms, and log replication processes.

PaxosRaftalgorithms
0 likes · 8 min read
Two-Phase Commit, Paxos, and Raft: Core Concepts and Workflows
Alibaba Cloud Developer
Alibaba Cloud Developer
Oct 27, 2020 · Fundamentals

Understanding EPaxos: The Leaderless Consensus Algorithm Explained

This article introduces EPaxos, a leaderless distributed consensus algorithm, explains its motivation from Paxos and Multi‑Paxos, describes its core concepts such as instance spaces, dependencies, and deterministic reordering, and discusses implementation challenges and practical considerations for engineers familiar with Paxos or Raft.

EPaxosRaftdistributed consensus
0 likes · 10 min read
Understanding EPaxos: The Leaderless Consensus Algorithm Explained
Architect
Architect
Sep 24, 2020 · Databases

Overview of TiDB Architecture: TiKV, PD, TiDB Server, and TiSpark

This article provides a comprehensive overview of TiDB's architecture, detailing the roles of TiKV Server, Placement Driver (PD), TiDB Server, and the TiSpark component, and explains how Raft ensures data consistency across the distributed database system.

Placement DriverRaftTiDB
0 likes · 11 min read
Overview of TiDB Architecture: TiKV, PD, TiDB Server, and TiSpark
Full-Stack DevOps & Kubernetes
Full-Stack DevOps & Kubernetes
Sep 18, 2020 · Cloud Native

Why Etcd Clusters Use Odd Nodes & What Happens During Leader Election

This article explains etcd’s Raft‑based consensus, why odd‑numbered nodes are recommended, details the leader election process with log excerpts, discusses split‑brain and consistency guarantees, and provides step‑by‑step instructions for generating certificates, deploying an etcd cluster, and using etcdctl commands.

CertificateCluster DeploymentEtcd
0 likes · 19 min read
Why Etcd Clusters Use Odd Nodes & What Happens During Leader Election
JD Cloud Developers
JD Cloud Developers
Sep 16, 2020 · Blockchain

Understanding Blockchain Consensus: POW, POS, DPOS, PBFT, Paxos & Raft Explained

This article surveys major blockchain consensus mechanisms—including Byzantine Fault Tolerance, Proof of Work, Proof of Stake, Delegated Proof of Stake, Practical BFT, Paxos, and Raft—detailing their principles, workflows, advantages, and challenges, and illustrates how they underpin distributed ledger security and performance.

BFTConsensusPOS
0 likes · 17 min read
Understanding Blockchain Consensus: POW, POS, DPOS, PBFT, Paxos & Raft Explained
Xiaokun's Architecture Exploration Notes
Xiaokun's Architecture Exploration Notes
Sep 7, 2020 · Fundamentals

How Raft Guarantees Strong Consistency: Leader Election & Log Replication Explained

This article provides a comprehensive overview of the Raft consensus algorithm, detailing its strong‑leader model, node states, leader election process, log replication mechanics, consistency checks, and single‑node configuration changes, while illustrating each concept with diagrams and code examples.

Consensus AlgorithmLog ReplicationRaft
0 likes · 25 min read
How Raft Guarantees Strong Consistency: Leader Election & Log Replication Explained
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 24, 2020 · Fundamentals

Why Raft Beats Paxos and EPaxos: A Deep Dive into Distributed Consensus

This article explores the evolution of distributed consensus—from Paxos to Multi‑Paxos, Raft, and EPaxos—examining their mechanisms, understandability, efficiency, availability, and suitable scenarios, while providing comparative analysis and thought‑provoking questions for practitioners in modern cloud systems.

EPaxosPaxosRaft
0 likes · 14 min read
Why Raft Beats Paxos and EPaxos: A Deep Dive into Distributed Consensus
Architect
Architect
Jun 7, 2020 · Fundamentals

Understanding Consistency Models and Distributed Consensus Protocols

This article explains the fundamentals of distributed consistency, covering weak and strong consistency, the CAP theorem, ACID and BASE models, and detailed overviews of 2PC, 3PC, Paxos, Raft, Gossip, NWR, Quorum, and Lease mechanisms, highlighting their trade‑offs and practical use cases.

2PCCAP theoremConsensus Protocols
0 likes · 16 min read
Understanding Consistency Models and Distributed Consensus Protocols
Java Architecture Diary
Java Architecture Diary
Jun 6, 2020 · Cloud Native

Explore Nacos 1.3.0: Embedded DB, New Raft Protocol, and High‑Availability

Nacos 1.3.0 introduces an embedded relational database, unified cluster management, an upgraded Raft consistency layer, security patches, Snowflake ID configuration, data migration guidance, new cluster addressing modes, and a set of Open‑API operations for Raft administration, all aimed at simplicity, performance, and high availability.

Embedded DatabaseRaftcluster management
0 likes · 10 min read
Explore Nacos 1.3.0: Embedded DB, New Raft Protocol, and High‑Availability
Xiao Lou's Tech Notes
Xiao Lou's Tech Notes
May 17, 2020 · Databases

How to Build a High‑Availability, High‑Performance Distributed ID Generator

Distributed systems need globally unique, often monotonic IDs, and this article examines common ID generation strategies—Snowflake, database auto‑increment, segment allocation, multi‑master databases, and Raft‑based consensus—evaluating each for high availability and high performance, and highlighting trade‑offs and implementation details.

Distributed IDRaftSnowflake
0 likes · 8 min read
How to Build a High‑Availability, High‑Performance Distributed ID Generator
360 Tech Engineering
360 Tech Engineering
Mar 31, 2020 · Backend Development

Implementing Raft Command Handling and Log Replication in Go

This article explains how to extend a Go implementation of the Raft consensus algorithm to handle client commands, replicate logs across the cluster, manage commit pipelines, and ensure election safety, while providing detailed code examples and discussion of underlying concepts.

ConsensusGoLog Replication
0 likes · 15 min read
Implementing Raft Command Handling and Log Replication in Go
360 Tech Engineering
360 Tech Engineering
Mar 20, 2020 · Backend Development

Implementing Raft Election Mechanism in Go – Part 2

This article, the second in a series on Raft, explains the election mechanism, server states, timers, RPC handling, and partition scenarios while providing complete Go code examples for the consensus module and its interactions.

ConsensusElectionGo
0 likes · 21 min read
Implementing Raft Election Mechanism in Go – Part 2
vivo Internet Technology
vivo Internet Technology
Mar 18, 2020 · Databases

Vivo Feature Storage Practice: Architecture, Design, and Future Directions Using Nebula Graph

Vivo’s feature‑storage platform, built on Nebula Graph’s Raft‑based, storage‑compute‑separated architecture and exposed via Redis‑compatible proxies, meets massive, low‑latency AI data demands while offering strong consistency, horizontal scalability, backup, active‑active replication, and a roadmap toward general‑purpose KV, cloud‑native integration, and advanced storage engines.

Distributed storageFeature StoreKV
0 likes · 21 min read
Vivo Feature Storage Practice: Architecture, Design, and Future Directions Using Nebula Graph
Efficient Ops
Efficient Ops
Mar 17, 2020 · Databases

Mastering etcd: From Basics to Cluster Deployment and Real‑World Use Cases

This comprehensive guide explains what etcd is, its Raft‑based architecture, key terminology, read/write flow, leader election, common scenarios such as service discovery and distributed locking, and provides step‑by‑step instructions for single‑node and multi‑node deployments with practical command examples.

Cluster DeploymentEtcdRaft
0 likes · 27 min read
Mastering etcd: From Basics to Cluster Deployment and Real‑World Use Cases
360 Tech Engineering
360 Tech Engineering
Mar 10, 2020 · Fundamentals

Introduction to Raft: A Comprehensive Overview of the Distributed Consensus Algorithm

This article provides a thorough introduction to the Raft consensus algorithm, explaining its purpose, core components such as state machine replication, log and consensus module, leader‑follower model, client interaction, fault‑tolerance considerations, the CAP trade‑off, and why Go is a suitable implementation language.

GoRaftState Machine Replication
0 likes · 11 min read
Introduction to Raft: A Comprehensive Overview of the Distributed Consensus Algorithm
dbaplus Community
dbaplus Community
Mar 8, 2020 · Databases

Why Distributed Databases Need a New Architecture: From Two‑Phase Commit to Raft

This article examines the pressures driving banks to redesign their core database systems, compares three distributed‑access approaches, explains the components of modern distributed databases, analyzes two‑phase and three‑phase commit issues, and evaluates consensus algorithms, CAP/BASE trade‑offs, GTM design, and point‑in‑time recovery.

CAP theoremGTMRaft
0 likes · 19 min read
Why Distributed Databases Need a New Architecture: From Two‑Phase Commit to Raft
Big Data Technology & Architecture
Big Data Technology & Architecture
Feb 28, 2020 · Databases

TiDB Technical Deep Dive – Storage, Compute, and Scheduling Architecture

This article provides a comprehensive technical overview of TiDB, covering its HTAP design, TiKV storage engine with RocksDB and Raft replication, the mapping of relational tables to key‑value pairs, MVCC implementation, transaction handling, and the PD scheduler that balances replicas, leaders, and hot spots across a distributed cluster.

HTAPKV storageRaft
0 likes · 31 min read
TiDB Technical Deep Dive – Storage, Compute, and Scheduling Architecture
Big Data Technology & Architecture
Big Data Technology & Architecture
Feb 19, 2020 · Fundamentals

Understanding CAP, Byzantine Fault Tolerance, PBFT, Paxos, and Raft Consensus Algorithms

This article explains the CAP theorem, illustrates the Byzantine Generals problem, and provides detailed overviews of PBFT, Paxos (including Multi‑Paxos), and Raft consensus algorithms, highlighting their phases, roles, and practical considerations for achieving consistency in distributed systems.

Byzantine Fault ToleranceConsensusPBFT
0 likes · 10 min read
Understanding CAP, Byzantine Fault Tolerance, PBFT, Paxos, and Raft Consensus Algorithms
Alibaba Cloud Native
Alibaba Cloud Native
Dec 9, 2019 · Cloud Native

Mastering etcd: History, Architecture, and Real‑World Use Cases

This article traces etcd’s evolution from its CoreOS origins, explains its Raft‑based distributed architecture, details its API groups, versioning and watch mechanisms, and showcases typical scenarios such as metadata storage, service discovery, leader election, and distributed coordination in cloud‑native environments.

Cloud NativeEtcdKey-Value Store
0 likes · 19 min read
Mastering etcd: History, Architecture, and Real‑World Use Cases
Huajiao Technology
Huajiao Technology
Oct 29, 2019 · Backend Development

Building a Scalable Distributed Cron: Google‑Level Design Simplified for Startups

This article examines Google's high‑availability distributed cron design, distills its core requirements and algorithms, and then presents a streamlined implementation for a startup using etcd and Raft, followed by a thoughtful discussion on whether early‑stage companies should adopt a middle‑platform strategy.

EtcdHigh AvailabilityRaft
0 likes · 10 min read
Building a Scalable Distributed Cron: Google‑Level Design Simplified for Startups
Alibaba Cloud Native
Alibaba Cloud Native
Sep 19, 2019 · Databases

How etcd’s Fully Concurrent Read Boosts Kubernetes Performance

This article reviews the evolution of etcd’s read‑write mechanisms, explains the “Fully Concurrent Read” feature introduced in etcd 3.4, and presents experimental results showing how it dramatically reduces expensive read latency and improves overall throughput in Kubernetes clusters.

BoltDBDistributed storageEtcd
0 likes · 14 min read
How etcd’s Fully Concurrent Read Boosts Kubernetes Performance
JD Retail Technology
JD Retail Technology
Jul 31, 2019 · Fundamentals

Consistency Levels and Consensus Algorithms: Paxos, ZAB, and Raft

This article explains distributed data consistency concepts, the CAP theorem, various consistency levels, and provides detailed overviews of three major consensus algorithms—Paxos, ZAB, and Raft—including their mechanisms, roles, and practical applications such as in CB‑SQL.

Data ReplicationPaxosRaft
0 likes · 18 min read
Consistency Levels and Consensus Algorithms: Paxos, ZAB, and Raft
JD Retail Technology
JD Retail Technology
Jul 19, 2019 · Databases

Optimizing Distributed Transactions in CB‑SQL: From Two‑Phase Commit to Parallel and Pipeline Commit

This article explains how CB‑SQL improves distributed transaction performance by introducing a transaction record table, parallel prepare requests, one‑phase commit for single‑shard writes, latch‑based consistent reads, transaction pipelines, and a staged parallel‑commit mode, dramatically reducing latency and I/O overhead.

CB-SQLLatchRaft
0 likes · 13 min read
Optimizing Distributed Transactions in CB‑SQL: From Two‑Phase Commit to Parallel and Pipeline Commit
JD Retail Technology
JD Retail Technology
Jul 3, 2019 · Databases

CB‑SQL: JD Retail’s Elastic Distributed Database Built on CockroachDB – Architecture and Implementation Details

The article introduces CB‑SQL, JD Retail’s next‑generation elastic database based on CockroachDB, and comprehensively explains its overview, layered architecture, storage replication, cluster management, MVCC, hybrid logical clocks, lock‑free distributed transactions, CDC changefeeds, and SQL interface support.

CDCCockroachDBMVCC
0 likes · 14 min read
CB‑SQL: JD Retail’s Elastic Distributed Database Built on CockroachDB – Architecture and Implementation Details
dbaplus Community
dbaplus Community
Feb 18, 2019 · Databases

How Do Fault‑Tolerant Transactions Work? Exploring Raft, KV Engines, and Concurrency Control

This article examines multiple fault‑tolerant transaction designs—RSM‑based KV, RSM‑based transactions, shared‑storage approaches, high‑availability KV layers, and single‑node engine extensions—comparing their replication strategies, lock handling, and performance trade‑offs while raising open questions about ordering and consistency.

KV storeRaftdistributed transactions
0 likes · 15 min read
How Do Fault‑Tolerant Transactions Work? Exploring Raft, KV Engines, and Concurrency Control
Youzan Coder
Youzan Coder
Jan 23, 2019 · Fundamentals

Consistency, CAP Theorem, and Distributed Consensus Protocols (2PC, 3PC, Paxos, Raft, Zookeeper)

The article explains how the CAP theorem forces trade‑offs between consistency, availability and partition tolerance, then surveys distributed commit protocols (2PC, 3PC) and consensus algorithms (Paxos, Raft, Zookeeper’s ZAB), and shows their practical use in systems such as ZanKV that combine Raft with RocksDB for strongly consistent, fault‑tolerant key‑value storage.

2PCCAP theoremConsensus Protocols
0 likes · 28 min read
Consistency, CAP Theorem, and Distributed Consensus Protocols (2PC, 3PC, Paxos, Raft, Zookeeper)
JD Tech
JD Tech
Sep 11, 2018 · Backend Development

Design and Implementation of Distributed Lock Services: Redis, ZooKeeper, and SharkLock

This article explains the principles, requirements, and implementation details of distributed lock services, comparing Redis and ZooKeeper approaches, and introduces SharkLock's design built on SharkStore with Raft-based replication, covering lock acquisition, release, reliability, scaling, and failover mechanisms.

Distributed LockRaftRedis
0 likes · 14 min read
Design and Implementation of Distributed Lock Services: Redis, ZooKeeper, and SharkLock
Architects' Tech Alliance
Architects' Tech Alliance
Sep 8, 2018 · Backend Development

Design and Implementation of Distributed Lock Services: Redis, ZooKeeper, and SharkLock

This article explains the principles of distributed locks, compares Redis‑based and ZooKeeper‑based implementations, discusses their limitations, and introduces the SharkLock system built on SharkStore with Raft‑based replication, detailing its reliability, dead‑lock prevention, and safety mechanisms.

Distributed LockRaftRedis
0 likes · 14 min read
Design and Implementation of Distributed Lock Services: Redis, ZooKeeper, and SharkLock
Youzan Coder
Youzan Coder
Aug 17, 2018 · Databases

Designing ZanKV: A Scalable Distributed KV Store Built on RocksDB, Raft, and Redis Protocol

This article details the design, architecture, and implementation of ZanKV—a high‑performance, distributed key‑value store that combines RocksDB storage, etcd‑Raft consensus, and a Redis‑compatible protocol, covering data partitioning, namespace isolation, expiration strategies, cross‑datacenter deployment, and performance tuning.

KV storePerformance TuningRaft
0 likes · 23 min read
Designing ZanKV: A Scalable Distributed KV Store Built on RocksDB, Raft, and Redis Protocol
ITPUB
ITPUB
May 16, 2018 · Databases

How RadonDB Merges Raft and MySQL for Scalable Cloud‑Native Databases

RadonDB is a next‑generation cloud‑native distributed relational database that combines the Raft consensus protocol with MySQL to deliver high availability, strong consistency, seamless scalability, and native support for OLTP, OLAP, distributed transactions, and comprehensive monitoring and backup features.

High AvailabilityRadonDBRaft
0 likes · 10 min read
How RadonDB Merges Raft and MySQL for Scalable Cloud‑Native Databases
Architecture Digest
Architecture Digest
Feb 15, 2018 · Databases

Design and Architecture of Zeppelin Distributed Block Storage System

This article presents an in‑depth overview of Zeppelin, a high‑availability, high‑performance block storage service, covering its motivation, online vs offline storage distinctions, data distribution strategies, centralized meta‑server design, replication policies, RocksDB‑based storage engine, Raft‑based consistency protocol, threading model, client request flow, and fault‑handling mechanisms.

Distributed storageHash PartitioningRaft
0 likes · 19 min read
Design and Architecture of Zeppelin Distributed Block Storage System
21CTO
21CTO
Jan 16, 2018 · Fundamentals

Why Distributed Consensus Is So Hard: From CAP to Byzantine Fault Tolerance

Distributed systems rely on consensus to ensure consistent results, but achieving it faces fundamental challenges such as network unreliability, node failures, and trade‑offs captured by the CAP theorem, FLP impossibility, and various algorithms like Paxos, Raft, and Byzantine Fault Tolerance, each balancing consistency, availability, and safety.

Byzantine Fault ToleranceCAP theoremPaxos
0 likes · 26 min read
Why Distributed Consensus Is So Hard: From CAP to Byzantine Fault Tolerance
Architecture Digest
Architecture Digest
Jan 16, 2018 · Fundamentals

Consistency, Consensus, and Reliability in Distributed Systems

This article explains the core challenges of achieving consistency in distributed systems, describes consensus algorithms such as Paxos and Raft, discusses theoretical limits like the FLP impossibility and CAP theorem, and shows how trade‑offs among consistency, availability, and partition tolerance shape practical system design.

CAP theoremFLP impossibilityPaxos
0 likes · 24 min read
Consistency, Consensus, and Reliability in Distributed Systems
21CTO
21CTO
Oct 9, 2017 · Databases

How Facebook Scales 2B Users with MySQL and the New Apollo NoSQL Engine

Since its inception, Facebook has relied on MySQL to handle data from over two billion users, but recent shifts toward NoSQL have led to the development of Apollo—a layered storage system inspired by Paxos, Raft, RocksDB, and custom APIs, aiming to improve scalability, latency, and fault tolerance.

ApolloFacebookNoSQL
0 likes · 8 min read
How Facebook Scales 2B Users with MySQL and the New Apollo NoSQL Engine
ITPUB
ITPUB
May 27, 2017 · Databases

Building a High‑Performance OAuth Token Service with Tarantool, Raft, and Sharding

This article explains how we designed and implemented a scalable OAuth token storage and refresh system using Tarantool’s in‑memory database, Raft leader election, sharding across multiple data centers, and a custom lightweight queue to handle high‑throughput token updates while maintaining consistency and fault tolerance.

OAuthRaftSharding
0 likes · 20 min read
Building a High‑Performance OAuth Token Service with Tarantool, Raft, and Sharding
Tencent Cloud Developer
Tencent Cloud Developer
Mar 13, 2017 · Cloud Computing

Technical Overview of Tencent Cloud CMQ: Architecture, Reliability, Consistency, and Scalability

Tencent Cloud CMQ is a Raft‑based distributed message queue that delivers high reliability, strong consistency, and horizontal scalability for finance‑grade workloads, using multi‑node broker sets with majority‑acknowledged writes, automatic leader election, unlimited buffering, full‑path tracing, while requiring application‑level idempotency and offering limited strict ordering.

CMQDistributed MessagingRaft
0 likes · 11 min read
Technical Overview of Tencent Cloud CMQ: Architecture, Reliability, Consistency, and Scalability
Architecture Digest
Architecture Digest
Feb 8, 2017 · Databases

The Evolution and Architecture of TiDB: From MySQL Compatibility to Distributed Storage

TiDB’s founder Huang Dongxu recounts the journey of building a MySQL‑compatible, distributed database—detailing early challenges, architectural decisions, the extensive testing, the adoption of Go, Rust, Raft, RocksDB, and the emphasis on metrics, cloud‑native design, and open‑source community collaboration.

MySQL CompatibilityRaftRocksDB
0 likes · 16 min read
The Evolution and Architecture of TiDB: From MySQL Compatibility to Distributed Storage
dbaplus Community
dbaplus Community
Jan 4, 2017 · Backend Development

How to Build a Raft‑Based Distributed Scheduler on Mesos with Go

This article explains the fundamentals of consensus in distributed systems, compares Paxos and Raft, and provides a step‑by‑step guide with code snippets on embedding the etcd/raft library into the open‑source Mesos scheduler Swan to achieve reliable multi‑node data synchronization.

Backend DevelopmentConsensusGo
0 likes · 14 min read
How to Build a Raft‑Based Distributed Scheduler on Mesos with Go
Architects' Tech Alliance
Architects' Tech Alliance
Dec 23, 2016 · Fundamentals

Advanced Distributed Systems Theory: Paxos, Raft, and Zab

This article provides an in‑depth exploration of distributed consensus protocols, detailing the basics of Paxos, extending to Multi‑Paxos, and comparing it with Raft and Zab while discussing leader election, quorum, lease mechanisms, and practical considerations for implementing these algorithms in real‑world systems.

ConsensusLeader ElectionPaxos
0 likes · 21 min read
Advanced Distributed Systems Theory: Paxos, Raft, and Zab
ITPUB
ITPUB
Aug 30, 2016 · Databases

How to Build a Distributed KV Store with Full ACID Guarantees

This talk walks through the evolution of databases, explains the challenges of building a distributed key‑value system that provides full ACID properties, and details the architectural components, sharding, migration, snapshot isolation, two‑phase commit, timestamp handling, and distributed transaction processing techniques.

ACIDKey-Value StoreNewSQL
0 likes · 13 min read
How to Build a Distributed KV Store with Full ACID Guarantees
Art of Distributed System Architecture Design
Art of Distributed System Architecture Design
Apr 7, 2016 · Cloud Native

Typical Use Cases and Implementation Details of etcd in Distributed Systems

This article introduces etcd, a highly‑available key‑value store based on the Raft algorithm, and explores its classic use cases such as service discovery, messaging, load balancing, distributed coordination, locks, queues, monitoring, leader election, and compares it with ZooKeeper, highlighting its simplicity, security, and cloud‑native advantages.

Cloud NativeEtcdKey-Value Store
0 likes · 19 min read
Typical Use Cases and Implementation Details of etcd in Distributed Systems