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Xiaokun's Architecture Exploration Notes

May 25, 2025 · Fundamentals

How Consensus, CAP, and BASE Shape High‑Availability Architecture

This article explains the role of consensus algorithms in achieving high‑availability through redundancy and automatic failover, clarifies distributed consistency, explores the CAP theorem and its C component, and introduces the BASE theory as a practical complement for eventual consistency in modern distributed systems.

BASE theoryCAP theoremConsensus

0 likes · 10 min read

How Consensus, CAP, and BASE Shape High‑Availability Architecture

DeWu Technology

Mar 26, 2025 · Fundamentals

Consistency Challenges and Solutions in Distributed Systems: CAP, BASE, RPC, and Messaging

To address consistency problems in distributed systems, the article explains CAP and BASE trade‑offs, shows how transactional RPC and messaging—using retries, RocketMQ two‑phase commits, Spring @TransactionalEventListener, or a local message log—can ensure atomic updates, and compares their reliability, latency, and performance impacts.

BASE theoryCAP theoremDistributed Consistency

0 likes · 12 min read

Consistency Challenges and Solutions in Distributed Systems: CAP, BASE, RPC, and Messaging

政采云技术

Apr 27, 2023 · Backend Development

Understanding CAP Theorem, BASE Theory, and Their Implementation with Zookeeper (CP) and Eureka (AP)

This article explains the CAP theorem and its trade‑offs, introduces the BASE model as a practical compromise, and demonstrates how Zookeeper implements a CP registration center while Eureka adopts an AP approach, illustrating the impact on consistency, availability, and partition tolerance in distributed systems.

BASE theoryCAP theoremEureka

0 likes · 12 min read

Understanding CAP Theorem, BASE Theory, and Their Implementation with Zookeeper (CP) and Eureka (AP)

Architect's Guide

Jan 15, 2023 · Backend Development

Distributed Transactions: Fundamentals, CAP & BASE Theories, and Solution Comparisons

This article explains the basic concepts of transactions, distinguishes local and distributed transactions, introduces the CAP and BASE theories, and compares major distributed‑transaction solutions such as 2PC, XA, Seata, TCC, reliable‑messaging and maximum‑effort notification, highlighting their trade‑offs.

2PCBASE theoryCAP theorem

0 likes · 40 min read

Distributed Transactions: Fundamentals, CAP & BASE Theories, and Solution Comparisons

Top Architect

Nov 7, 2022 · Backend Development

Distributed Transaction Solutions: 2PC, TCC, Seata, Reliable Messaging, and Maximum‑Effort Notification

This article explains the fundamentals of transactions, the challenges of distributed transactions, introduces ACID, CAP and BASE theories, and compares practical solutions such as two‑phase commit, TCC, Seata, reliable message‑based eventual consistency, and maximum‑effort notification, concluding with a comparative analysis of their trade‑offs.

2PCBASE theoryCAP theorem

0 likes · 42 min read

Distributed Transaction Solutions: 2PC, TCC, Seata, Reliable Messaging, and Maximum‑Effort Notification

Architect

Dec 20, 2021 · Fundamentals

Understanding Distributed Systems: Zookeeper, 2PC/3PC, Consensus Algorithms, CAP and BASE Theories

This article explains the evolution from centralized to distributed architectures, the role of Zookeeper in solving consistency problems, the mechanics and drawbacks of 2‑phase and 3‑phase commits, and key consensus algorithms such as Paxos, Raft, ZAB, as well as CAP and BASE theories that guide practical system design.

2PC3PCBASE theory

0 likes · 23 min read

Understanding Distributed Systems: Zookeeper, 2PC/3PC, Consensus Algorithms, CAP and BASE Theories

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 theoremPaxos

0 likes · 21 min read

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

Architecture Digest

Nov 3, 2020 · Backend Development

Data Consistency in Microservices: Transaction Management and Implementation Patterns

This article introduces the limitations of traditional local and distributed transactions for microservices, explains the BASE theory, and details four practical patterns—reliable event notification, maximum‑effort notification, business compensation, and TCC—providing code examples, diagrams, and a comparative table to guide developers in achieving eventual consistency across microservice architectures.

BASE theoryMicroservicesTransaction Management

0 likes · 19 min read

Data Consistency in Microservices: Transaction Management and Implementation Patterns

Java Architect Essentials

Oct 13, 2020 · Backend Development

Data Consistency in Microservices: Transaction Management Patterns and Practices

The article reviews microservice data consistency challenges, explains why traditional distributed transactions like 2PC/3PC are unsuitable, introduces the BASE theory, and details four implementation patterns—reliable event notification, maximum effort notification, business compensation, and TCC—to achieve eventual consistency.

BASE theoryMicroservicesTransaction Management

0 likes · 19 min read

Data Consistency in Microservices: Transaction Management Patterns and Practices

Top Architect

Jul 8, 2020 · Fundamentals

Distributed System Characteristics and Solutions for Distributed Transaction Consistency

This article explains the key characteristics of distributed systems, introduces the CAP and BASE theories, compares strong, weak and eventual consistency models, and reviews common distributed transaction solutions such as two‑phase commit, TCC and message‑based approaches, highlighting their trade‑offs and practical considerations.

BASE theoryCAP theoremTwo-Phase Commit

0 likes · 13 min read

Distributed System Characteristics and Solutions for Distributed Transaction Consistency

Architect's Tech Stack

May 26, 2019 · Fundamentals

Understanding CAP Theorem, Consistency Levels, and BASE Theory in Distributed Systems

This article explains the CAP theorem, the trade‑offs among consistency, availability and partition tolerance, describes strong, weak and eventual consistency models, and introduces the BASE approach as a practical alternative for large‑scale distributed systems.

BASE theoryCAP theoremDatabase

0 likes · 12 min read

Understanding CAP Theorem, Consistency Levels, and BASE Theory in Distributed Systems

Architecture Digest

Sep 7, 2018 · Databases

Understanding Distributed Transactions: From XA to CAP, BASE, 2PC, 3PC, TCC, and Saga

The article explains the necessity of transactions, traces their origins from database XA specifications to modern distributed systems, compares CAP and BASE theories, and reviews mainstream solutions such as two‑phase commit, three‑phase commit, TCC, asynchronous messaging, and the Saga pattern.

BASE theoryCAP theoremTwo-Phase Commit

0 likes · 14 min read

Understanding Distributed Transactions: From XA to CAP, BASE, 2PC, 3PC, TCC, and Saga

Architecture Digest

Jul 11, 2018 · Cloud Native

Understanding Modern Distributed Architecture: SOA, Microservices, Service Mesh, CAP & BASE Theories, and High‑Availability Design

This article explains the evolution and core concepts of mainstream distributed architectures—including SOA, microservices, and service mesh—covers fundamental consistency theories such as CAP and BASE, and outlines practical high‑availability and scalability techniques for building resilient cloud‑native systems.

BASE theoryCAP theoremCloud Native

0 likes · 17 min read

Understanding Modern Distributed Architecture: SOA, Microservices, Service Mesh, CAP & BASE Theories, and High‑Availability Design