This article explains the essential design principles of a TCC (Try‑Confirm‑Cancel) distributed transaction framework, covering the necessity of RM local transactions, integration with Spring's TransactionManager, fault‑recovery mechanisms, idempotency guarantees, and handling of parallel Try/Confirm/Cancel operations.
Microservice architectures struggle with traditional ACID transactions, so this article reviews local and distributed transaction basics, explains why 2PC/3PC are unsuitable, introduces the BASE model, and details four practical consistency patterns—reliable event, async event, business compensation, and TCC—highlighting their mechanisms, advantages, and drawbacks.
This article shares practical guidance on microservice benefits, common pitfalls such as stability and data consistency issues, and detailed solutions including circuit breakers, service degradation tactics, TCC distributed transactions, transactional messaging with RocketMQ, seamless data migration, and full‑stack APM monitoring.
This article introduces five common distributed transaction patterns—XA two‑phase commit, TCC, local message table, reliable message eventual consistency, and max‑effort notification—explains their principles, advantages, drawbacks, and provides interview questions and suggested answers for each.
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.
This article explains the fundamentals of distributed transactions, compares five major solutions—including XA two‑phase commit, TCC, Saga, message‑based approaches, and maximum‑effort notification—covers their architectures, advantages, drawbacks, and provides guidance on selecting the right model for micro‑service systems.
This article explores the fundamentals of distributed transactions, comparing traditional two‑phase commit with flexible approaches like reliable‑message eventual consistency, TCC, and best‑effort notification, and provides detailed design patterns, implementation steps, and trade‑offs for building robust backend systems.
This article walks through setting up Seata for distributed transaction management in a Spring Cloud microservices project, covering concepts of AT, TCC, and Saga modes, configuration of Seata server and clients, code examples for transaction handling, and a practical e‑commerce demo.
This article explains the fundamentals of distributed transactions, compares local and global transaction models, examines protocols like XA and 2PC, introduces flexible transaction patterns such as TCC and compensable operations, and evaluates reliable message‑based solutions for achieving eventual consistency.
This article explains the necessity of distributed transactions in modern systems, introduces the CAP and BASE consistency theories, and reviews practical solutions such as the XA two‑phase commit, TCC compensation model, and message‑queue based eventual consistency approaches.
This article explores the complexities of building a generic TCC distributed transaction framework, emphasizing the need for RM-local transaction integration, Spring TransactionManager takeover, fault‑recovery mechanisms, idempotency guarantees, and proper handling of Try/Confirm/Cancel phases to ensure global consistency.
This article explains how Ant Financial tackled cross‑service and cross‑database data‑consistency challenges caused by horizontal sharding and service‑oriented decomposition, introduces its home‑grown distributed‑transaction middleware and the open‑source Seata project with AT, TCC, Saga and XA modes, and shares performance‑optimisation and high‑availability practices.
This article walks through building an e‑commerce platform using microservices, covering module decomposition, domain‑driven design, service splitting, technology stack choices, distributed transaction strategies, circuit‑breaker patterns, centralized configuration, monitoring, and capacity planning to guide developers from concept to deployment.
This article explains Alipay's TCC (Try‑Confirm‑Cancel) distributed transaction model, its two‑phase workflow, a concrete transfer example, common failure scenarios, and the pros and cons of using TCC in backend systems.
This article, excerpted from the book "Software Architecture Design: Integrating Large‑Scale Website Technical and Business Architecture," systematically presents seven practical solutions—including two eventual‑consistency approaches, two compromise methods, TCC, state‑machine retry with idempotence, and reconciliation—to address the pervasive challenges of distributed transactions in micro‑service systems.
This article introduces the TCC (Try‑Confirm‑Cancel) distributed transaction model, explains its three phases with real‑world e‑commerce examples, compares it to other solutions, and shows how mature frameworks ensure eventual consistency and automatic rollback in failure scenarios.
This article explains the ACID properties of transactions, contrasts them with the CAP theorem and BASE model, and then explores practical distributed‑transaction solutions such as two‑phase commit, TCC, and reliable asynchronous messaging, including their advantages, drawbacks, and implementation tips.
This article analyzes the challenges of implementing a generic TCC distributed transaction framework using Spring, emphasizing the need for RM‑local transaction integration, transaction manager takeover, fault recovery, idempotency, and proper handling of Try/Confirm/Cancel operations.
This article explains the challenges of distributed transactions in microservice architectures, covering database transaction fundamentals, the CAP and BASE theories, and evaluates various solutions such as 2PC, TCC, local message tables, MQ transactional messages, Sagas, and introduces the open‑source .NET CAP framework.
This article explains Hmily’s core features, the four key techniques that give it high performance—including Disruptor‑based log handling, asynchronous confirm/cancel execution, ThreadLocal caching, and GuavaCache usage—and provides step‑by‑step guidance on integrating the framework with Dubbo, Spring Cloud, or Motan.
This article explains the fundamentals of distributed transactions, covering ACID and CAP theory, the BASE model, and compares common solutions such as two‑phase commit, TCC, local message tables, MQ transactional messages, and Sagas, while also introducing the open‑source .NET CAP framework with its features and limitations.
This article explains the fundamentals of distributed transactions, why they arise in modern micro‑service architectures, outlines the ACID properties, presents typical use cases such as payments and order processing, and compares common implementation approaches like 2PC, message‑based eventual consistency, and TCC.
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.
This article explains the challenges of preserving ACID properties in distributed environments, introduces CAP and BASE trade‑offs, reviews industry transaction models such as XA, 2PC, weak XA, BED, TCC and Saga, and details how ShardingSphere implements and plans to evolve support for these distributed transaction mechanisms.
This article introduces the TCC (Try‑Confirm‑Cancel) distributed transaction model, explains its two‑phase workflow, and outlines six essential design considerations—including two‑phase operation splitting, empty rollback handling, suspension control, idempotency, data visibility, and concurrency—while sharing Ant Financial’s decade‑long practical experience and solutions.
This article details Ant Financial's multi‑year development of a comprehensive distributed transaction framework—including TCC, FMT, and XA models—designed to ensure financial‑grade consistency, high performance, and seamless cloud‑native integration for massive, latency‑sensitive payment and accounting services.
This article reviews Ant Financial's evolution of distributed transaction solutions—from early SOA consistency issues to the high‑performance TCC model, the developer‑friendly FMT approach, and the real‑time XA integration with OceanBase—highlighting architectural decisions, optimizations, and practical outcomes.
This article explains the fundamentals of database transactions, the ACID properties, and how they extend to distributed environments, covering two‑phase commit, three‑phase commit, and the TCC model while discussing their advantages, limitations, and practical examples.
This article explains the fundamentals of database transactions, the ACID properties, and how they are implemented in relational systems before exploring distributed transaction challenges and solutions such as 2PC, 3PC, TCC, and message‑based approaches.
This article explains the fundamentals of relational database transactions, the ACID properties, and various distributed transaction protocols such as 2PC, 3PC, TCC, message‑based approaches, and 1PC, while discussing their advantages, drawbacks, and practical considerations.
This article clarifies core concepts such as transaction compensation, CAP theorem, idempotency, and BASE, compares rigid ACID‑based transactions with flexible BASE‑based approaches, and provides best‑practice guidance for choosing and implementing 2PC, TCC, and asynchronous assurance patterns in distributed systems.
This article explores the challenges of distributed transactions in microservice architectures, explains consistency theories like CAP and BASE, compares classic 2PC with eBay's event‑queue approach, TCC compensation, and cache‑based eventual consistency, and offers practical guidance for choosing the right solution.
The article explains common interview questions on distributed systems and compares transaction coordination methods, detailing the two‑phase commit drawbacks and introducing three patterns—TCC, asynchronous assurance, and maximum‑effort notification—along with their advantages, usage scenarios, and practical considerations.
This article walks through the evolution of distributed transaction architectures—from simple single-database transactions, through post-commit multi-database approaches and two-phase commit, to TCC and eventual-consistency patterns—illustrating each method with game-style purchase examples, diagrams, and practical implementation tips.
