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Top Architect
Top Architect
Jun 2, 2022 · Databases

Reasonable Strategies for Database and Cache Read/Write Consistency

The article discusses how to achieve reasonable read/write consistency between databases and caches by emphasizing cache expiration, eventual consistency, analyzing the Cache‑Aside pattern, evaluating four update‑order options, recommending the "update‑DB‑then‑delete‑cache" approach, and suggesting async deletion via message queues and distributed locks to handle concurrency and cache breakdown.

Consistencycache-asidedistributed-lock
0 likes · 19 min read
Reasonable Strategies for Database and Cache Read/Write Consistency
IT Architects Alliance
IT Architects Alliance
May 21, 2022 · Backend Development

Cache Usage Techniques and Design Strategies

This article explains how caching can accelerate read/write performance and reduce backend load, analyzes its benefits and costs, and details practical design patterns such as update policies, granularity control, penetration, bottom‑hole, avalanche, and hot‑key optimizations for reliable high‑performance systems.

ConsistencyDistributed Systemsbackend optimization
0 likes · 13 min read
Cache Usage Techniques and Design Strategies
政采云技术
政采云技术
May 19, 2022 · Databases

Distributed Transaction Consistency Solutions

This article explains the fundamentals of distributed transactions, covering ACID, CAP and BASE theories, and reviews various consistency solutions such as two‑phase commit, three‑phase commit, TCC, local message tables, MQ approaches and the Seata framework, highlighting their advantages and drawbacks.

2PCCAPConsistency
0 likes · 18 min read
Distributed Transaction Consistency Solutions
Sohu Tech Products
Sohu Tech Products
May 18, 2022 · Fundamentals

Understanding Strong vs. Weak Consistency in Java's ConcurrentHashMap

This article explains the concepts of strong and weak consistency, their roots in visibility and ordering within the Java Memory Model, and how Java 8’s ConcurrentHashMap uses volatile fields, CAS, and unsafe operations to achieve strong consistency for put/get while retaining weak consistency for operations like size().

ConcurrentHashMapConsistencyJava
0 likes · 14 min read
Understanding Strong vs. Weak Consistency in Java's ConcurrentHashMap
Architects Research Society
Architects Research Society
May 6, 2022 · Fundamentals

Understanding the CAP Theorem and How PACELC Extends It

The article explains the CAP theorem’s three properties—consistency, availability, and partition tolerance—its implications for distributed systems, highlights its limitations, introduces the PACELC extension that adds latency versus consistency trade‑offs when no partition exists, and provides real‑world database examples.

AvailabilityCAP theoremConsistency
0 likes · 7 min read
Understanding the CAP Theorem and How PACELC Extends It
Wukong Talks Architecture
Wukong Talks Architecture
May 5, 2022 · Backend Development

Deep Dive into Nacos Distro Consistency Protocol: Design, Mechanisms, and Source Code Analysis

This article explains the design principles, six core mechanisms, asynchronous replication, periodic synchronization, new‑node sync, and local read strategy of Nacos's Distro consistency protocol, illustrating how AP/CP choices and the JRaft protocol ensure high availability in a distributed service registry.

APConsistencyDistributed Systems
0 likes · 13 min read
Deep Dive into Nacos Distro Consistency Protocol: Design, Mechanisms, and Source Code Analysis
Top Architect
Top Architect
May 1, 2022 · Backend Development

Cache Consistency Challenges and Practical Strategies for Database‑Redis Integration

The article explains why high‑traffic systems store data in databases but use fast caches like Redis, outlines the inherent consistency problems between cache and database, evaluates four update‑delete strategies with concurrency scenarios, and recommends practical solutions such as post‑update cache eviction, delayed double deletion, expiration policies, message queues, and binlog listeners to achieve eventual consistency.

BackendConsistencydistributed-systems
0 likes · 19 min read
Cache Consistency Challenges and Practical Strategies for Database‑Redis Integration
IT Architects Alliance
IT Architects Alliance
Apr 30, 2022 · Backend Development

Cache Consistency Strategies and Best Practices for Database‑Cache Synchronization

This article explains why caching is essential for high‑read workloads, describes the consistency challenges when data resides in both MySQL and Redis, compares four cache‑update strategies, and offers practical recommendations such as using expiration, delayed double‑delete, message queues, and binlog subscription to achieve eventual consistency.

BackendConsistencycaching
0 likes · 20 min read
Cache Consistency Strategies and Best Practices for Database‑Cache Synchronization
Architect's Journey
Architect's Journey
Apr 13, 2022 · Fundamentals

Is Classifying Distributed Systems as CP or AP a False Dichotomy?

The article revisits the CAP theorem, explains linearizable consistency and strict availability, demonstrates with concrete data‑center examples why the CP/AP split is often misleading, and argues that latency concerns and broader failure modes make the binary classification of distributed systems impractical.

AvailabilityCAP theoremCP vs AP
0 likes · 10 min read
Is Classifying Distributed Systems as CP or AP a False Dichotomy?
IT Services Circle
IT Services Circle
Apr 7, 2022 · Databases

Database and Cache Dual-Write Consistency: Common Solutions and Pitfalls

This article examines the problem of data inconsistency when writing to both a database and a cache, outlines four typical dual‑write strategies, analyzes their drawbacks in high‑concurrency scenarios, and recommends the most reliable approach—writing to the database first followed by cache deletion with retry mechanisms.

CacheConsistencyMessaging
0 likes · 18 min read
Database and Cache Dual-Write Consistency: Common Solutions and Pitfalls
Yanxuan Tech Team
Yanxuan Tech Team
Apr 7, 2022 · Backend Development

Mastering Server‑Side Caching: From Local to Distributed Multilevel Strategies

This article explains why caching is essential for reducing CPU and I/O pressure, outlines key cache attributes such as throughput and hit rate, compares popular local cache libraries, describes distributed cache options, and details the design, consistency, monitoring, and hot‑key handling of a transparent multilevel cache architecture.

ConsistencyHeliosdistributed cache
0 likes · 20 min read
Mastering Server‑Side Caching: From Local to Distributed Multilevel Strategies
Top Architect
Top Architect
Mar 22, 2022 · Backend Development

Cache Update Strategies: Consistency, Concurrency, and Failure Handling

The article analyzes various cache update strategies—including delete‑then‑write, write‑then‑delete, and asynchronous binlog subscription—examining their impact on system throughput, concurrency safety, failure scenarios, and fault detection to ensure data consistency between cache and database.

BackendCacheConsistency
0 likes · 6 min read
Cache Update Strategies: Consistency, Concurrency, and Failure Handling
DaTaobao Tech
DaTaobao Tech
Mar 9, 2022 · Cloud Native

Distributed System Consistency Handling

The article explains how distributed systems maintain request consistency by employing idempotent IDs, state‑machine tracking, snapshot recording, and coordinated error‑handling strategies—including retries, queries, and messaging—while also addressing read/write separation limits, reconciliation, and disaster‑recovery measures to prevent duplicate actions and state divergence.

ConsistencyDistributed SystemsError Handling
0 likes · 18 min read
Distributed System Consistency Handling
Code Ape Tech Column
Code Ape Tech Column
Feb 21, 2022 · Backend Development

Cache Consistency Issues and Solutions: Cache‑Aside Pattern, Lazy Deletion, and High‑Concurrency Queue Design

This article explains the fundamental cache‑aside pattern, why lazy cache deletion is preferred over immediate updates, analyzes simple and complex cache‑database inconsistency scenarios, and proposes a high‑concurrency queue‑based solution with practical considerations for backend systems.

ConsistencyLazy Deletioncache-aside
0 likes · 11 min read
Cache Consistency Issues and Solutions: Cache‑Aside Pattern, Lazy Deletion, and High‑Concurrency Queue Design
Top Architect
Top Architect
Feb 18, 2022 · Backend Development

Ensuring Data Consistency Between Cache and Database: Strategies and Trade‑offs

The article analyzes the problem of data inconsistency when using caches such as Redis or local memory alongside a database, classifies data by real‑time requirements, compares four write‑through/write‑behind strategies, and proposes practical solutions like delayed double‑delete, message‑queue compensation, and binlog‑driven cache updates.

BackendCacheConsistency
0 likes · 8 min read
Ensuring Data Consistency Between Cache and Database: Strategies and Trade‑offs
IT Architects Alliance
IT Architects Alliance
Feb 17, 2022 · Databases

Understanding Consistency in Distributed Transactions: Strong vs. Weak, CAP Theory, and NewSQL Approaches

This article explains the concept of consistency in distributed transactions, compares strong and weak consistency, relates it to the CAP theorem, and explores theoretical and practical approaches—including XA, NewSQL, and MVCC—to achieve stronger consistency across databases and micro‑services.

ACIDCAP theoremConsistency
0 likes · 13 min read
Understanding Consistency in Distributed Transactions: Strong vs. Weak, CAP Theory, and NewSQL Approaches
Java Backend Technology
Java Backend Technology
Jan 24, 2022 · Backend Development

How to Solve Double‑Write Consistency Issues with Message Queues

This article examines the pitfalls of writing to multiple data stores simultaneously—such as consistency and atomicity problems—and proposes a generic solution using change data capture and message queues to keep databases, Redis, Elasticsearch, and Hadoop synchronized.

Consistencydata synchronizationdouble write
0 likes · 7 min read
How to Solve Double‑Write Consistency Issues with Message Queues
Big Data Technology & Architecture
Big Data Technology & Architecture
Jan 18, 2022 · Big Data

Data Warehouse Data Quality Measurement Standards

The article outlines four key dimensions for evaluating data warehouse data quality—correctness, completeness, timeliness, and consistency—explains common consistency issues such as differing metric values across models, cross‑dimensional aggregations, and real‑time versus batch calculations, and proposes organizational and review mechanisms to mitigate these problems.

Big DataConsistencyData Governance
0 likes · 9 min read
Data Warehouse Data Quality Measurement Standards
Architects Research Society
Architects Research Society
Dec 5, 2021 · Databases

Understanding Sequential, Causal, and Eventual Consistency Models

This article explains the concepts of sequential, causal, and eventual consistency models, illustrating their definitions, guarantees, and practical examples—including process interactions and real‑world scenarios—while comparing their strengths, trade‑offs, and related consistency guarantees such as monotonic reads, writes, and read‑your‑writes.

ConsistencyDistributed Systemscausal consistency
0 likes · 10 min read
Understanding Sequential, Causal, and Eventual Consistency Models
Java Architect Essentials
Java Architect Essentials
Nov 19, 2021 · Fundamentals

A Comprehensive Guide to Learning Distributed Systems

This article provides a thorough overview of distributed systems, explaining their definition, core concepts such as partition and replication, key challenges, essential characteristics, typical components and protocols, a practical request flow example, and a curated list of real‑world implementations to help readers build a solid learning roadmap.

ConsistencyDistributed SystemsPartition
0 likes · 17 min read
A Comprehensive Guide to Learning Distributed Systems
ITPUB
ITPUB
Nov 5, 2021 · Databases

Why Distributed Databases Face Consistency Challenges and How to Address Them

The article explains how distributed database systems appear as a single logical database but operate over a network of nodes, detailing failures, stale reads, consistency models, architecture anomalies, sharding, replication, and various read/write scenarios that illustrate the complexity of achieving strong consistency.

CAP theoremConsistencydistributed databases
0 likes · 16 min read
Why Distributed Databases Face Consistency Challenges and How to Address Them
Alibaba Cloud Developer
Alibaba Cloud Developer
Oct 26, 2021 · Fundamentals

Jepsen Uncovered: A Practical Guide to Linearizability Testing

This article explains the fundamentals of Jepsen testing, compares it with TLA+, describes its architecture and workflow, illustrates how to apply Jepsen for linearizability verification of distributed systems such as locks, and offers practical guidance on integrating Jepsen or building custom testing frameworks.

ConsistencyDistributed SystemsJepsen
0 likes · 17 min read
Jepsen Uncovered: A Practical Guide to Linearizability Testing
IT Architects Alliance
IT Architects Alliance
Oct 24, 2021 · Databases

Database Capacity Planning and Scaling with ScyllaDB

This article explains why database capacity planning is challenging and presents a systematic approach—including workload analysis, performance modeling, consistency considerations, and node scaling decisions—using the open‑source NoSQL database ScyllaDB to guide accurate capacity estimation.

ConsistencyNoSQLPerformance Modeling
0 likes · 14 min read
Database Capacity Planning and Scaling with ScyllaDB
21CTO
21CTO
Oct 21, 2021 · Databases

Why Is Database Capacity Planning So Hard? Simplify with ScyllaDB

This article explains why sizing a database cluster is challenging, outlines a step‑by‑step methodology for estimating workload, configuration and performance, discusses the impact of consistency levels, secondary indexes, materialized views and maintenance, and shows how ScyllaDB can be used to model and simplify capacity planning.

ConsistencyDatabase CapacityNoSQL
0 likes · 16 min read
Why Is Database Capacity Planning So Hard? Simplify with ScyllaDB
Java Architect Essentials
Java Architect Essentials
Oct 18, 2021 · Fundamentals

Fundamentals of Distributed Systems: Models, Replication, Consistency, and Protocols

This article introduces core concepts of distributed systems, including node and replica models, various consistency levels, data distribution strategies, lease and quorum mechanisms, replica control protocols such as primary‑secondary, two‑phase commit, MVCC, Paxos, and the CAP theorem, providing a comprehensive overview for architects.

CAP theoremConsensusConsistency
0 likes · 54 min read
Fundamentals of Distributed Systems: Models, Replication, Consistency, and Protocols
Top Architect
Top Architect
Sep 26, 2021 · Fundamentals

Fundamentals of Distributed Systems: Concepts, Replication, Consistency, and Protocols

This article provides a comprehensive overview of distributed system fundamentals, covering system models, node concepts, failure types, replication strategies, consistency levels, data distribution methods, replica control protocols such as primary‑secondary, two‑phase commit, lease‑based caching, quorum, MVCC, Paxos, and the CAP theorem.

ConsistencyDistributed SystemsLease
0 likes · 54 min read
Fundamentals of Distributed Systems: Concepts, Replication, Consistency, and Protocols
IT Architects Alliance
IT Architects Alliance
Sep 6, 2021 · Databases

Comprehensive Overview of Data Models, Storage Engines, Transactions, Consistency, and Replication in Modern Databases

This article provides a detailed summary of database concepts including data models (relational, document, graph), storage engine architectures (page‑oriented B‑tree, log‑structured LSM), transaction mechanisms, isolation levels, distributed transaction protocols, partitioning strategies, indexing, consistency models, and consensus algorithms such as Lamport timestamps and Raft.

ConsistencyData ModelsStorage Engines
0 likes · 29 min read
Comprehensive Overview of Data Models, Storage Engines, Transactions, Consistency, and Replication in Modern Databases
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Aug 6, 2021 · Backend Development

Ensuring Consistency Between Redis Cache and MySQL Database: Patterns and Practical Solutions

This article explains how to maintain data consistency between Redis cache and MySQL database by describing strong, weak, and eventual consistency, three classic cache patterns (Cache‑Aside, Read‑Through/Write‑Through, Write‑Behind), and practical solutions such as delayed double deletion, retry mechanisms, and binlog‑based asynchronous eviction.

Consistencycaching-patterns
0 likes · 13 min read
Ensuring Consistency Between Redis Cache and MySQL Database: Patterns and Practical Solutions
Continuous Delivery 2.0
Continuous Delivery 2.0
Aug 6, 2021 · R&D Management

Consistency as the Essential Path to R&D Efficiency

The talk explains that achieving consistency in development processes, tool platforms, and personnel capabilities is essential for scaling software organizations without losing productivity, describing entropy, random complexity, the EPC model, and CLCT metric as practical ways to improve R&D efficiency.

ConsistencyDevOpsEngineering management
0 likes · 19 min read
Consistency as the Essential Path to R&D Efficiency
Top Architect
Top Architect
Aug 3, 2021 · Fundamentals

Design and Considerations of Distributed File Systems

This article provides a comprehensive overview of distributed file systems, covering their historical evolution, essential requirements such as POSIX compliance, persistence, scalability, and security, and comparing centralized (e.g., GFS) and decentralized (e.g., Ceph) architectures along with strategies for high availability, performance optimization, and data consistency.

ConsistencyDistributed File SystemScalability
0 likes · 19 min read
Design and Considerations of Distributed File Systems
IT Architects Alliance
IT Architects Alliance
Jul 25, 2021 · Fundamentals

Fundamentals of Distributed Systems: Concepts, Replication, Consistency, and Core Protocols

This article provides a comprehensive overview of distributed system fundamentals, covering concepts such as nodes, replicas, consistency models, data distribution strategies, lease and quorum mechanisms, two‑phase commit, MVCC, Paxos, and the CAP theorem, while discussing their practical engineering trade‑offs and failure handling.

CAP theoremConsistencyDistributed Systems
0 likes · 54 min read
Fundamentals of Distributed Systems: Concepts, Replication, Consistency, and Core Protocols
Architects' Tech Alliance
Architects' Tech Alliance
Jul 18, 2021 · Fundamentals

Fundamentals of Distributed Systems: Concepts, Replication, Consistency, and Core Protocols

This article provides a comprehensive overview of distributed system fundamentals, covering system models, replicas, performance and availability metrics, data distribution strategies, replica protocols such as lease, quorum, two‑phase commit, MVCC, Paxos, and the CAP theorem, with practical engineering considerations.

CAP theoremConsistencyLease
0 likes · 53 min read
Fundamentals of Distributed Systems: Concepts, Replication, Consistency, and Core Protocols
Sohu Tech Products
Sohu Tech Products
Jun 30, 2021 · Fundamentals

Raft Log Replication: Format, Process, and Consistency Guarantees

This article explains the Raft consensus algorithm’s log format, the step‑by‑step log replication process, how leaders ensure consistency through forced overwrites, and details the AppendEntries RPC parameters, illustrated with diagrams and examples.

ConsistencyLog ReplicationRaft
0 likes · 11 min read
Raft Log Replication: Format, Process, and Consistency Guarantees
Ctrip Technology
Ctrip Technology
Jun 24, 2021 · Backend Development

Design and Implementation of Distributed Cache with Eventual and Strong Consistency at Ctrip Finance

This article presents Ctrip Finance's design of a unified high‑availability Redis cache service, covering both eventual‑consistency and strong‑consistency scenarios, the overall architecture, data‑accuracy, completeness and availability mechanisms, lock handling, fault‑tolerant updates, and operational recovery strategies.

ConsistencyMicroservicesdistributed cache
0 likes · 26 min read
Design and Implementation of Distributed Cache with Eventual and Strong Consistency at Ctrip Finance
Java Interview Crash Guide
Java Interview Crash Guide
Jun 9, 2021 · Backend Development

Designing a Universal Static Data Cache for Microservice Architectures

This article examines the challenges of caching low‑frequency static data in microservice systems and proposes a comprehensive solution that combines business services, Redis, persistent queues, and consistency‑checking programs to achieve high‑performance, near‑real‑time data access while mitigating cache‑related risks.

ConsistencyMicroservicesQueue
0 likes · 13 min read
Designing a Universal Static Data Cache for Microservice Architectures
IT Architects Alliance
IT Architects Alliance
Jun 6, 2021 · Fundamentals

Design Principles and Architecture of Distributed File Systems

This article provides a comprehensive overview of distributed file systems, covering their historical evolution, essential requirements, architectural models with and without central nodes, persistence strategies, scalability, high availability, performance optimization, security mechanisms, and additional considerations such as space allocation, file deletion, small‑file handling, and deduplication.

ConsistencyDistributed File SystemScalability
0 likes · 21 min read
Design Principles and Architecture of Distributed File Systems
Programmer DD
Programmer DD
Jun 1, 2021 · Fundamentals

What Makes Distributed File Systems Tick? Design Principles and Architecture Explained

This article explores the core concepts, design requirements, architectural models, scalability, high availability, performance optimization, and security considerations of distributed file systems, comparing centralized and decentralized approaches while highlighting practical solutions for persistence, consistency, and fault tolerance.

ConsistencyDistributed File SystemScalability
0 likes · 21 min read
What Makes Distributed File Systems Tick? Design Principles and Architecture Explained
Java Backend Technology
Java Backend Technology
May 27, 2021 · Backend Development

How to Ensure Cache‑Database Consistency: Patterns and Pitfalls Explained

This article explains cache‑database consistency challenges, outlines three classic caching patterns, compares delete‑versus‑update strategies, discusses operation ordering, and presents three practical solutions—including delayed double delete, retry mechanisms, and binlog‑based asynchronous eviction—to help maintain data integrity in distributed systems.

BackendCacheConsistency
0 likes · 11 min read
How to Ensure Cache‑Database Consistency: Patterns and Pitfalls Explained
macrozheng
macrozheng
May 26, 2021 · Backend Development

How to Ensure Cache‑Database Consistency: Patterns, Pitfalls, and Solutions

This article explains the concepts of strong, weak, and eventual consistency, introduces three classic cache patterns (Cache‑Aside, Read‑Through/Write‑Through, Write‑Behind), and discusses practical strategies such as delayed double‑delete, retry mechanisms, and binlog‑based asynchronous eviction to keep Redis and MySQL data in sync.

CacheConsistencydistributed-systems
0 likes · 11 min read
How to Ensure Cache‑Database Consistency: Patterns, Pitfalls, and Solutions
Code Ape Tech Column
Code Ape Tech Column
May 19, 2021 · Backend Development

How Transparent Multilevel Cache (TMC) Eliminates Hotspot Bottlenecks in High‑Traffic E‑Commerce

The article explains Youzan’s Transparent Multilevel Cache (TMC), detailing its architecture, hotspot detection, local caching, consistency mechanisms, and real‑world performance gains during flash‑sale events, showing how it reduces cache pressure and improves latency for Java‑based services.

CacheConsistencyDistributed Systems
0 likes · 16 min read
How Transparent Multilevel Cache (TMC) Eliminates Hotspot Bottlenecks in High‑Traffic E‑Commerce
Tencent Cloud Developer
Tencent Cloud Developer
May 12, 2021 · Databases

Evolution and Architecture of Distributed Databases: A TDSQL Case Study

The talk traces the evolution of distributed databases—from early shared‑memory and shared‑nothing designs through New‑SQL breakthroughs—to Tencent’s HTAP‑oriented TDSQL, highlighting its strong‑consistency architecture, anomaly taxonomy, and performance advantages over systems like Google Spanner while addressing modern scalability and hardware challenges.

ConsistencyDatabase ArchitectureHTAP
0 likes · 22 min read
Evolution and Architecture of Distributed Databases: A TDSQL Case Study
Big Data Technology & Architecture
Big Data Technology & Architecture
May 11, 2021 · Big Data

Data Quality: Dimensions, Rules, and Constraints

The article explains the importance of data quality in the big data era, defines key quality dimensions such as completeness, uniqueness, validity, consistency, accuracy, timeliness, and credibility, and details how each dimension can be measured and enforced through specific constraints and validation rules.

Big DataConsistencyData Governance
0 likes · 9 min read
Data Quality: Dimensions, Rules, and Constraints
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Apr 25, 2021 · Databases

Overview of Database System Design

This article provides a comprehensive overview of database system design, covering the historical evolution, classification of relational and NoSQL databases, common architectures, consistency models, indexing techniques, storage formats, compression, and practical considerations for selecting and optimizing database solutions.

ConsistencySystem Designarchitecture
0 likes · 45 min read
Overview of Database System Design
Top Architect
Top Architect
Apr 24, 2021 · Fundamentals

Fundamentals of Distributed Systems: Models, Replication, Consistency, and Core Protocols

This article provides a comprehensive overview of distributed system fundamentals, covering node models, replica concepts, various consistency levels, data distribution strategies, lease-based caching, quorum mechanisms, two‑phase commit, MVCC, Paxos consensus, and the CAP theorem, illustrating each with practical examples and diagrams.

CAP theoremConsensusConsistency
0 likes · 54 min read
Fundamentals of Distributed Systems: Models, Replication, Consistency, and Core Protocols
Java Interview Crash Guide
Java Interview Crash Guide
Apr 19, 2021 · Fundamentals

What You Need to Know About Distributed Systems: Theory, Consistency, Transactions & Redis

This comprehensive guide covers the core concepts of distributed systems—including CAP theory, consistency models, transaction protocols like 2PC/3PC and TCC, Redis features, persistence options, expiration strategies, memory eviction policies, distributed locking with Redis and Zookeeper, as well as an overview of Kafka's architecture and reliability mechanisms.

ConsistencyDistributed SystemsMessage Queue
0 likes · 34 min read
What You Need to Know About Distributed Systems: Theory, Consistency, Transactions & Redis
Java Architect Essentials
Java Architect Essentials
Apr 6, 2021 · Backend Development

Distributed Transaction Solutions: 2PC, 3PC, XA, TCC, Saga, Local Message Table, Transactional Messages, and Seata

This article explains the importance of distributed transactions in micro‑service architectures, reviews ACID properties, compares various solutions such as 2PC/3PC, XA, local message tables, transactional messages, TCC, Saga, and introduces the Seata framework with its AT, TCC, and Saga modes, while also discussing consistency versus consensus with Paxos.

2PCConsistencyDistributed Transactions
0 likes · 14 min read
Distributed Transaction Solutions: 2PC, 3PC, XA, TCC, Saga, Local Message Table, Transactional Messages, and Seata
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Apr 6, 2021 · Backend Development

Cache Consistency Strategies: TTL, Delayed Double Delete, Cache‑Aside, and Message‑Queue Approaches

This article examines cache consistency challenges in Redis-backed systems and compares several update strategies—including TTL, delayed double‑delete, cache‑aside, and message‑queue approaches—detailing their workflows, code examples, advantages, and drawbacks to guide backend developers toward reliable cache invalidation.

BackendCacheConsistency
0 likes · 7 min read
Cache Consistency Strategies: TTL, Delayed Double Delete, Cache‑Aside, and Message‑Queue Approaches
MaGe Linux Operations
MaGe Linux Operations
Apr 5, 2021 · Backend Development

Mastering Distributed Transactions: Protocols, Patterns, and Seata Explained

This article explores the fundamentals of distributed transactions in microservice architectures, detailing ACID properties, classic protocols like 2PC/3PC and XA, modern patterns such as TCC, Saga, local message tables, transaction messages, and the Seata framework, while comparing their trade‑offs with Paxos consensus.

2PCConsistencyDistributed Transactions
0 likes · 16 min read
Mastering Distributed Transactions: Protocols, Patterns, and Seata Explained
21CTO
21CTO
Apr 2, 2021 · Databases

Choosing the Right Database Architecture: Principles, Schemes, and Consistency Solutions

This article outlines core database architecture principles, compares four common deployment schemes (master‑slave, dual‑master, master‑slave with read/write separation, and hybrid), and presents practical consistency solutions for both primary‑replica and DB‑cache mismatches, followed by personal evolution insights.

Consistencyarchitecturedatabase
0 likes · 11 min read
Choosing the Right Database Architecture: Principles, Schemes, and Consistency Solutions
ITPUB
ITPUB
Apr 2, 2021 · Databases

Choosing the Right MySQL Architecture: Master‑Standby, Dual‑Master, and Consistency Strategies

This article examines core MySQL architecture principles—high availability, performance, consistency, and scalability—then compares four common deployment patterns, analyzes their trade‑offs, and presents practical consistency solutions for both master‑slave replication and cache synchronization, ending with personal insights on evolution and sharding.

ConsistencyDatabase ArchitectureRead-Write Separation
0 likes · 12 min read
Choosing the Right MySQL Architecture: Master‑Standby, Dual‑Master, and Consistency Strategies
Wukong Talks Architecture
Wukong Talks Architecture
Mar 18, 2021 · Fundamentals

Understanding Distributed Theory and Algorithms: Importance, Core Concepts, and Learning Path

This article explains why distributed theory and algorithms are crucial for architects, outlines the four foundational theories and eight key protocols, discusses their four evaluation dimensions, and provides a step‑by‑step learning roadmap illustrated with stories and practical examples.

CAP theoremConsistencyDistributed Systems
0 likes · 10 min read
Understanding Distributed Theory and Algorithms: Importance, Core Concepts, and Learning Path
IT Xianyu
IT Xianyu
Mar 2, 2021 · Fundamentals

Understanding ZooKeeper: Purpose, Features, and Design Goals

This article explains why ZooKeeper was created, its role in simplifying distributed application development, key characteristics such as high performance, high availability, and consistency, and outlines the fundamental problems it solves in multi‑process coordination across networked systems.

ConsistencyDistributed CoordinationZooKeeper
0 likes · 7 min read
Understanding ZooKeeper: Purpose, Features, and Design Goals
Tencent Cloud Developer
Tencent Cloud Developer
Feb 26, 2021 · Fundamentals

Distributed Consistency Algorithms: CAP, BASE, Paxos, and Raft

From CAP and BASE trade‑offs to the rigorous Paxos consensus and the more approachable Raft protocol, this article explains how modern distributed systems achieve consistency despite partitions, failures, and latency, detailing roles, phases, and safety guarantees that underpin reliable micro‑service architectures.

BASE theoryCAP theoremConsistency
0 likes · 21 min read
Distributed Consistency Algorithms: CAP, BASE, Paxos, and Raft
58UXD
58UXD
Feb 26, 2021 · Frontend Development

How to Build a Consistent UI for Multi‑Business‑Line Messaging Center Micro‑Chat

This article outlines the background, composition issues, and a three‑principle design system—consistency, interaction reasonableness, and flexibility—used to create a unified UI for 58’s multi‑business‑line messaging center micro‑chat, detailing component specifications, navigation rules, typography, colors, and layout guidelines.

Consistencydesign systemfrontend
0 likes · 6 min read
How to Build a Consistent UI for Multi‑Business‑Line Messaging Center Micro‑Chat
Code Ape Tech Column
Code Ape Tech Column
Feb 19, 2021 · Databases

Understanding Timestamps in Distributed Transactions: TSO, TrueTime, Lamport Clock, and HLC

This article explains the role of timestamps in distributed transaction processing, comparing implementations such as MVCC‑based TSO, Google’s TrueTime, Lamport logical clocks, and Hybrid Logical Clocks, and discusses their impact on linearizability, consistency guarantees, and practical designs like TiDB Async Commit.

ConsistencyDistributed TransactionsHLC
0 likes · 14 min read
Understanding Timestamps in Distributed Transactions: TSO, TrueTime, Lamport Clock, and HLC
Code Ape Tech Column
Code Ape Tech Column
Jan 29, 2021 · Fundamentals

Fundamentals of Distributed Systems: Concepts, Replication, Consistency, and Protocols

This article provides a comprehensive overview of distributed system fundamentals, covering core concepts such as nodes, replicas, consistency models, data distribution strategies, lease and quorum mechanisms, two‑phase commit, MVCC, Paxos, and the CAP theorem, along with practical considerations for designing robust, scalable services.

CAP theoremConsensusConsistency
0 likes · 53 min read
Fundamentals of Distributed Systems: Concepts, Replication, Consistency, and Protocols
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Jan 28, 2021 · Fundamentals

Distributed Systems Essentials: Models, Replicas, Consistency & Protocols

This comprehensive guide explores the core concepts of distributed systems, covering node models, replica strategies, consistency levels, data distribution techniques, lease-based caching, quorum mechanisms, logging, two‑phase commit, MVCC, Paxos consensus, and the CAP theorem, providing practical insights for building robust scalable architectures.

ConsensusConsistencyDistributed Systems
0 likes · 55 min read
Distributed Systems Essentials: Models, Replicas, Consistency & Protocols
Alibaba Cloud Developer
Alibaba Cloud Developer
Jan 20, 2021 · Fundamentals

How to Build Efficient Cross‑Region Distributed Consistency Systems

This article examines the challenges of cross‑region distributed consistency, reviews industry solutions such as direct deployment, learner roles, and partitioned services, and introduces Alibaba’s log‑mirroring decoupled architecture, evaluating trade‑offs in latency, scalability, availability, and consistency for global systems.

ConsistencyPaxoscross-region
0 likes · 20 min read
How to Build Efficient Cross‑Region Distributed Consistency Systems
Java Interview Crash Guide
Java Interview Crash Guide
Jan 19, 2021 · Databases

Choosing the Right Database Architecture: Pros, Cons, and Consistency Solutions

This article outlines core database architecture principles—high availability, performance, consistency, and scalability—and evaluates four common schemes (primary‑backup, dual‑master, master‑slave with read/write separation, and hybrid), followed by detailed consistency‑resolution strategies and personal insights.

ConsistencyDual MasterMaster‑Slave
0 likes · 9 min read
Choosing the Right Database Architecture: Pros, Cons, and Consistency Solutions
Open Source Linux
Open Source Linux
Jan 18, 2021 · Operations

Why ZooKeeper Is Essential for Distributed Application Coordination

This article explains ZooKeeper's purpose, core features, and design goals, showing how it simplifies distributed application development by providing high‑performance, highly available coordination services such as naming, locks, leader election, and configuration management while hiding low‑level complexities.

APIConsistencyDistributed Coordination
0 likes · 10 min read
Why ZooKeeper Is Essential for Distributed Application Coordination
Selected Java Interview Questions
Selected Java Interview Questions
Jan 15, 2021 · Backend Development

Designing High‑Performance, High‑Availability Flash‑Sale (秒杀) Systems: Architecture, Consistency, and Optimization

This article explains how to design a flash‑sale system that handles massive concurrent requests by focusing on high performance through dynamic‑static separation, hotspot optimization, and code‑level tuning, while ensuring strong consistency for inventory and maintaining high availability via traffic shaping, fault‑tolerance, and operational best practices.

Consistencyflash salehigh performance
0 likes · 27 min read
Designing High‑Performance, High‑Availability Flash‑Sale (秒杀) Systems: Architecture, Consistency, and Optimization
Liangxu Linux
Liangxu Linux
Dec 29, 2020 · Backend Development

Understanding ZooKeeper: Architecture, Data Model, Sessions, and Leader Election

ZooKeeper is an open‑source distributed coordination service that provides primitives for synchronization, configuration management, and naming, featuring a hierarchical data model of znodes, session handling, one‑time watches, strong consistency guarantees, leader election via Zab protocol, and detailed roles of leader, follower, and observer.

ConsistencyDistributed CoordinationWatches
0 likes · 17 min read
Understanding ZooKeeper: Architecture, Data Model, Sessions, and Leader Election
Code Ape Tech Column
Code Ape Tech Column
Dec 29, 2020 · Fundamentals

Understanding Distributed Consistency: CAP, BASE, 2PC, 3PC, Paxos, Raft, ZAB, and NWR Model

This article explains the challenges of distributed systems such as node failures and network anomalies, then introduces the CAP theorem, BASE theory, two‑phase and three‑phase commit protocols, and details consensus algorithms including Paxos, Raft, ZAB, and Amazon Dynamo's NWR model, highlighting their trade‑offs and practical usage.

2PC3PCCAP theorem
0 likes · 37 min read
Understanding Distributed Consistency: CAP, BASE, 2PC, 3PC, Paxos, Raft, ZAB, and NWR Model
Selected Java Interview Questions
Selected Java Interview Questions
Dec 28, 2020 · Backend Development

Eureka vs Zookeeper: AP vs CP Trade‑offs in Service Registry Design

The article compares Eureka and Zookeeper as service registry solutions, explaining how Eureka follows an AP model with high availability and eventual consistency, while Zookeeper adopts a CP model prioritizing strong consistency, and discusses their suitable scenarios, limitations, and design considerations for distributed systems.

AvailabilityCAP theoremConsistency
0 likes · 10 min read
Eureka vs Zookeeper: AP vs CP Trade‑offs in Service Registry Design
Java Backend Technology
Java Backend Technology
Dec 10, 2020 · Databases

Why Your New Master‑Slave DB May Not Reflect Recent Writes—and How to Fix It

This article explains a real‑world case where a newly added mapping rule didn't appear immediately due to master‑slave replication lag, walks through the evolution of database architectures from single‑node to read‑write separation, and presents several practical strategies to mitigate consistency issues caused by replication delay.

ConsistencyMaster‑SlaveRead-Write Separation
0 likes · 9 min read
Why Your New Master‑Slave DB May Not Reflect Recent Writes—and How to Fix It
Tencent Cloud Developer
Tencent Cloud Developer
Nov 19, 2020 · Backend Development

Kafka Message Queue Reliability Design and Implementation

The article thoroughly explains Kafka’s message‑queue reliability design and implementation, covering use‑case scenarios, core concepts, storage format, producer acknowledgment settings, broker replication mechanisms (ISR, HW, LEO), consumer delivery semantics, the epoch solution for synchronization, and practical configuration guidelines for various consistency and availability requirements.

BrokerConsistencyConsumer
0 likes · 15 min read
Kafka Message Queue Reliability Design and Implementation
Architects' Tech Alliance
Architects' Tech Alliance
Nov 7, 2020 · Fundamentals

Design Considerations and Architecture of Distributed File Systems

This article examines the evolution, core requirements, architectural models (centralized and decentralized), persistence strategies, scalability, high availability, performance optimization, security mechanisms, and additional design trade‑offs of distributed file systems, providing a comprehensive overview for architects and engineers.

ConsistencyDistributed File SystemScalability
0 likes · 19 min read
Design Considerations and Architecture of Distributed File Systems
Java Backend Technology
Java Backend Technology
Nov 5, 2020 · Backend Development

How to Eliminate Double‑Write Consistency Problems with Message Queues and CDC

This article explores common data‑synchronization challenges such as double‑write consistency and atomicity issues across databases, Redis, Elasticsearch and Hadoop, and presents a generic solution using ordered message queues and change‑data‑capture middleware to ensure reliable, consistent updates.

Backend DevelopmentChange Data CaptureConsistency
0 likes · 8 min read
How to Eliminate Double‑Write Consistency Problems with Message Queues and CDC
Architecture Digest
Architecture Digest
Oct 23, 2020 · Fundamentals

Understanding Consistency Algorithms: Paxos, Raft, ZAB, and Gossip

This article explains why data consistency is essential in distributed systems, defines consistency, compares strong and eventual consistency, and details the design and operation of major algorithms such as Paxos, Multi‑Paxos, Raft, ZAB, and Gossip with illustrative examples and diagrams.

Consistencyalgorithmdistributed-systems
0 likes · 11 min read
Understanding Consistency Algorithms: Paxos, Raft, ZAB, and Gossip
High Availability Architecture
High Availability Architecture
Oct 13, 2020 · Cloud Native

Service Discovery: Call Patterns, Consistency Trade‑offs, and Health‑Check Designs

This article examines the motivations for service discovery in microservice architectures, compares client‑side and server‑side discovery patterns, discusses consistency versus availability trade‑offs (CAP, CP vs AP), and reviews various health‑check mechanisms, graceful up/down strategies, metadata considerations, and high‑availability designs.

ConsistencyMicroserviceshealth check
0 likes · 14 min read
Service Discovery: Call Patterns, Consistency Trade‑offs, and Health‑Check Designs
Efficient Ops
Efficient Ops
Oct 9, 2020 · Fundamentals

Understanding the CAP Theorem Through a Real‑World Memory Service Story

This article uses a relatable memory‑service scenario to illustrate the CAP theorem, explaining how consistency, availability, and partition tolerance cannot all be achieved simultaneously in distributed systems and exploring practical trade‑offs through successive design attempts.

AvailabilityCAP theoremConsistency
0 likes · 9 min read
Understanding the CAP Theorem Through a Real‑World Memory Service Story
dbaplus Community
dbaplus Community
Sep 23, 2020 · Databases

How JinS Achieves Multi‑Region Data Consistency and High Performance

Facing scalability limits, disaster risks, and latency in single‑region setups, OPPO built the JinS data‑sync framework, detailing its multi‑region challenges, design principles, modular architecture, consistency models, crash‑safe 2PC mechanisms, file‑queue optimizations, relay‑log handling, and performance gains over open‑source and commercial alternatives.

ConsistencyDatabase ReplicationDistributed Systems
0 likes · 21 min read
How JinS Achieves Multi‑Region Data Consistency and High Performance
Top Architect
Top Architect
Sep 17, 2020 · Backend Development

Cache Consistency Strategies: Cache‑Aside Pattern, Deleting vs. Updating Cache, and Queue‑Based Solutions for High Concurrency

The article explains how distributed cache‑aside patterns work, why deleting stale cache entries is often preferable to updating them, analyzes basic and complex cache‑database inconsistency scenarios, and proposes a JVM‑queue‑driven, single‑threaded update mechanism with practical considerations for high‑concurrency environments.

BackendConsistencyDistributed Systems
0 likes · 11 min read
Cache Consistency Strategies: Cache‑Aside Pattern, Deleting vs. Updating Cache, and Queue‑Based Solutions for High Concurrency
21CTO
21CTO
Sep 12, 2020 · Fundamentals

Why Distributed Systems Mirror Single‑Node Concurrency and How to Avoid Common Pitfalls

This article explains how concurrency issues that appear in single‑threaded programs become amplified in distributed systems, covering consistency models, network reliability, clock synchronization, fault detection, backpressure, and cascading failures, and offers practical design and testing strategies to build resilient architectures.

Consistencyconcurrencyfault tolerance
0 likes · 19 min read
Why Distributed Systems Mirror Single‑Node Concurrency and How to Avoid Common Pitfalls
Architect
Architect
Sep 9, 2020 · Backend Development

Cache Aside Pattern and Solutions for Cache‑Database Consistency in High‑Concurrency Environments

The article explains the classic Cache Aside pattern, why deleting rather than updating cache is preferred, analyzes basic and complex cache inconsistency scenarios, and proposes a queue‑based lazy update solution with practical considerations for read‑write blocking, request routing, and hotspot handling in high‑traffic systems.

ConsistencyDistributed SystemsQueue
0 likes · 11 min read
Cache Aside Pattern and Solutions for Cache‑Database Consistency in High‑Concurrency Environments
IT Architects Alliance
IT Architects Alliance
Aug 31, 2020 · Databases

Distributed SQL: Features, Core Characteristics, and Cloud-Native Requirements

The article explains the evolution of database architecture toward distributed SQL, outlining its seven core features such as scalability, consistency, elasticity, geo‑replication, SQL support, data locality, and multi‑cloud capability, while also describing essential database functions and practical considerations for cloud‑native deployments.

Cloud DatabasesConsistencyDistributed SQL
0 likes · 9 min read
Distributed SQL: Features, Core Characteristics, and Cloud-Native Requirements
MaGe Linux Operations
MaGe Linux Operations
Aug 31, 2020 · Databases

Why Distributed SQL is the Future of Cloud Databases: 7 Key Features Explained

Distributed SQL databases combine the reliability of traditional relational systems with cloud-native scalability, offering seven core traits—scalability, consistency, elasticity, geo-replication, SQL support, data locality, and multi‑cloud operation—while still meeting essential database functions such as manageability, optimization, security, and integration.

Cloud DatabasesConsistencyDistributed SQL
0 likes · 9 min read
Why Distributed SQL is the Future of Cloud Databases: 7 Key Features Explained
Architecture Digest
Architecture Digest
Aug 24, 2020 · Backend Development

Cache Consistency Strategies: Cache Aside Pattern, Deleting vs Updating Cache, and Queue‑Based Solutions for High Concurrency

This article explains the cache‑aside pattern, why deleting cache entries is often preferable to updating them, outlines basic and complex cache‑database inconsistency scenarios, and presents a queue‑driven approach with practical considerations for maintaining data consistency in high‑concurrency backend systems.

CacheConsistencyQueue
0 likes · 10 min read
Cache Consistency Strategies: Cache Aside Pattern, Deleting vs Updating Cache, and Queue‑Based Solutions for High Concurrency
Top Architect
Top Architect
Aug 18, 2020 · Fundamentals

Fundamentals of Distributed Systems: Models, Replication, Consistency, and Core Protocols

This comprehensive article explains the core concepts of distributed systems—including node modeling, failure types, replica strategies, consistency levels, performance metrics, data distribution techniques, lease mechanisms, quorum, logging, two‑phase commit, MVCC, Paxos, and the CAP theorem—providing a solid foundation for designing robust, scalable architectures.

CAP theoremConsensusConsistency
0 likes · 53 min read
Fundamentals of Distributed Systems: Models, Replication, Consistency, and Core Protocols
Architect's Tech Stack
Architect's Tech Stack
Aug 14, 2020 · Operations

ZooKeeper Interview Questions and Core Concepts

This article provides a comprehensive overview of ZooKeeper, covering its role as a distributed coordination service, consistency guarantees, ZAB protocol, Znode types, watcher mechanism, ACL permissions, chroot feature, session management, server roles, data synchronization, deployment modes, and typical use cases in distributed systems.

ACLConsistencyDistributed Coordination
0 likes · 19 min read
ZooKeeper Interview Questions and Core Concepts
Programmer DD
Programmer DD
Aug 13, 2020 · Backend Development

How to Solve Distributed Cache Consistency Issues with Lazy Updates and Queues

This article explains the classic Cache‑Aside pattern, analyzes common cache‑database consistency problems in high‑concurrency scenarios, and presents a lazy‑update queue solution that deletes stale cache entries, routes updates through internal JVM queues, and mitigates read‑blocking and hotspot issues.

ConsistencyDistributed SystemsQueue
0 likes · 11 min read
How to Solve Distributed Cache Consistency Issues with Lazy Updates and Queues
Alibaba Cloud Developer
Alibaba Cloud Developer
Aug 4, 2020 · Fundamentals

How NFSv4 Guarantees Consistent File Locks Across Clients

This article explains the principles behind NFS file‑lock state view consistency, covering NFSv4's stateful design, the SeqId mechanism, SunRPC handling of duplicate requests, and how signal interruptions are managed to keep client and server lock views synchronized.

ConsistencyDistributed File SystemFile Lock
0 likes · 10 min read
How NFSv4 Guarantees Consistent File Locks Across Clients