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distributed transactions

303 articles · Page 3 of 4
ITPUB
ITPUB
Mar 25, 2021 · Backend Development

Why a TCC Framework Must Own the Spring TransactionManager

This article examines the challenges of building a generic TCC distributed‑transaction framework on Spring, explaining why every TCC service must participate in RM‑local transactions, why the framework should intercept the Spring TransactionManager, how to handle fault recovery, idempotency of Confirm/Cancel, and the pitfalls of relying on Cancel for rollback, concluding with practical recommendations.

SpringTCCTransactionManager
0 likes · 18 min read
Why a TCC Framework Must Own the Spring TransactionManager
Beike Product & Technology
Beike Product & Technology
Mar 24, 2021 · Backend Development

Optimizing Distributed Transactions with Seata in a Government Talent Housing System

This article details how the government talent housing system adopted the open‑source Seata distributed‑transaction framework, identified severe performance bottlenecks during large‑scale batch operations, and applied a series of optimizations—including query‑lock rewriting, rollback‑info compression, JDBC batch tuning, and multithreaded processing—to reduce a 30000‑record transaction from 280 seconds to under 7 seconds, achieving production‑grade reliability.

JavaMySQLSeata
0 likes · 8 min read
Optimizing Distributed Transactions with Seata in a Government Talent Housing System
IT Architects Alliance
IT Architects Alliance
Mar 7, 2021 · Databases

Mastering Distributed Transactions: From ACID to TCC and Sharding Strategies

This article provides a comprehensive technical guide to distributed transactions, covering ACID fundamentals, consistency models, sharding techniques, CAP and BASE theories, and detailed implementations of two‑phase, three‑phase, and TCC protocols, while highlighting their advantages, limitations, and practical considerations.

BASE theoryCAP theoremTCC
0 likes · 23 min read
Mastering Distributed Transactions: From ACID to TCC and Sharding Strategies
JD Cloud Developers
JD Cloud Developers
Mar 5, 2021 · Databases

How Transparent Sharding Middleware Powers NewSQL: Core Functions Explained

This article explains the fundamentals of transparent sharding middleware in NewSQL systems, covering data partitioning strategies, read/write separation, the complete SQL processing pipeline, protocol adaptation for MySQL/PostgreSQL, distributed transaction models such as XA, Saga and TCC, and essential database governance and online scaling techniques.

Database GovernanceDatabase MiddlewareNewSQL
0 likes · 28 min read
How Transparent Sharding Middleware Powers NewSQL: Core Functions Explained
Code Ape Tech Column
Code Ape Tech Column
Feb 5, 2021 · Backend Development

How to Solve Distributed Transactions in Microservices: From 2PC to TCC and Reliable Messaging

This article analyzes the challenges of distributed transactions in microservice architectures, explains ACID, CAP and BASE theories, compares consistency models, and evaluates practical solutions such as two‑phase commit, local message tables, TCC, and reliable messaging with code examples and implementation details.

2PCBASE theoryCAP theorem
0 likes · 26 min read
How to Solve Distributed Transactions in Microservices: From 2PC to TCC and Reliable Messaging
Tencent Cloud Middleware
Tencent Cloud Middleware
Jan 8, 2021 · Cloud Native

Why Centralized Architecture Evolves to Microservices: Banking Insights

This article recaps a technical conference where experts explained how traditional centralized banking systems transition to microservice architectures, compared rigid and flexible distributed transaction models, examined IBM mainframe designs, and highlighted practical considerations for service mesh and cloud‑native deployments.

IBMbanking architecturedistributed transactions
0 likes · 17 min read
Why Centralized Architecture Evolves to Microservices: Banking Insights
Top Architect
Top Architect
Jan 4, 2021 · Backend Development

Understanding the Saga Pattern for Distributed Data Consistency in Microservices

This article explains the importance of data consistency in distributed microservice systems, introduces the Saga pattern as a solution, compares it with two‑phase commit and TCC, and details its architecture, recovery mechanisms, and implementation considerations within ServiceComb.

Data ConsistencyTCCdistributed transactions
0 likes · 19 min read
Understanding the Saga Pattern for Distributed Data Consistency in Microservices
ITPUB
ITPUB
Dec 24, 2020 · Databases

How TDSQL Achieves Multi‑Level Strong Consistency with 4×‑3× Performance Gains

This article explains how Tencent's TDSQL database tackles the combined challenges of transaction and distributed consistency by introducing a multi‑level strong consistency model that delivers several‑fold performance improvements over Spanner, CockroachDB, and native Greenplum while preserving ACID guarantees.

Database ResearchTDSQLdistributed transactions
0 likes · 12 min read
How TDSQL Achieves Multi‑Level Strong Consistency with 4×‑3× Performance Gains
Java Interview Crash Guide
Java Interview Crash Guide
Dec 17, 2020 · Databases

Mastering Data Sharding: When and How to Split Your Database

This article explains the concepts, types, advantages, and drawbacks of vertical and horizontal database sharding, discusses the challenges such as distributed transactions, cross‑node joins, pagination, global primary‑key generation, migration, and provides practical guidelines and case studies for deciding when and how to apply sharding.

Horizontal ShardingVertical Shardingdatabase partitioning
0 likes · 28 min read
Mastering Data Sharding: When and How to Split Your Database
Senior Brother's Insights
Senior Brother's Insights
Dec 2, 2020 · Databases

Mastering Data Sharding: When, How, and What to Watch Out For

This comprehensive guide explains why and when to split relational databases, details vertical and horizontal sharding techniques, discusses associated challenges such as distributed transactions, cross‑node joins, pagination, global primary keys, and offers practical solutions and middleware options.

Global ID GenerationHorizontal ShardingVertical Sharding
0 likes · 24 min read
Mastering Data Sharding: When, How, and What to Watch Out For
Programmer DD
Programmer DD
Nov 28, 2020 · Backend Development

Deep Dive into ShardingSphere XA Distributed Transaction Support and Atomikos Integration

This article provides a comprehensive technical analysis of ShardingSphere's XA distributed transaction capabilities, covering the CAP theory, X/Open DTP model, MySQL XA support, JTA mapping, Atomikos initialization, transaction lifecycle (begin, getConnection, commit, rollback), and the recovery mechanism with detailed code snippets and diagrams.

AtomikosJTAJava
0 likes · 34 min read
Deep Dive into ShardingSphere XA Distributed Transaction Support and Atomikos Integration
vivo Internet Technology
vivo Internet Technology
Nov 25, 2020 · Backend Development

An Overview of the Seata Distributed Transaction Framework and Its Modes

Seata is an open‑source Java framework that simplifies distributed transactions by offering a Transaction Coordinator, embedded Transaction and Resource Managers, and four modes—AT, TCC, Saga, and XA—each with distinct consistency and performance trade‑offs, enabling high‑concurrency, zero‑intrusion handling of multi‑node operations.

AT ModeJavaSAGA
0 likes · 15 min read
An Overview of the Seata Distributed Transaction Framework and Its Modes
Java High-Performance Architecture
Java High-Performance Architecture
Nov 12, 2020 · Backend Development

Understanding SAGA Distributed Transactions: Choreography vs Orchestration

This article explains the concept and implementation approaches of SAGA as a distributed transaction solution, covering the problem definition, the two strategies—Choreography and Orchestration—including their workflows, event handling, state machine coordination, advantages, drawbacks, and references to Alibaba's Seata framework.

ChoreographySAGASeata
0 likes · 7 min read
Understanding SAGA Distributed Transactions: Choreography vs Orchestration
Java Backend Technology
Java Backend Technology
Nov 7, 2020 · Databases

How Seata’s AT Mode Solves Distributed Transaction Challenges

This article explains the fundamentals of single- and multi-data-source transactions, reviews common distributed-transaction solutions such as 2PC, 3PC, TCC, transaction-status tables and message-queue based eventual consistency, and then details Seata’s AT mode implementation, including its workflow, undo-log mechanism, and isolation handling.

AT ModeSeataTCC
0 likes · 32 min read
How Seata’s AT Mode Solves Distributed Transaction Challenges
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Nov 6, 2020 · Databases

Distributed Transaction Solutions and Seata AT Mode Implementation

This article explains the limitations of single‑database transactions in multi‑data‑source micro‑service scenarios, reviews common distributed‑transaction models such as 2PC, 3PC, TCC, status‑table and message‑queue based final consistency, and details the implementation of Seata's AT mode for achieving global ACID properties.

2PCAT ModeSeata
0 likes · 30 min read
Distributed Transaction Solutions and Seata AT Mode Implementation
Aikesheng Open Source Community
Aikesheng Open Source Community
Oct 15, 2020 · Databases

MySQL Middleware Deep Dive: Sharding vs Middleware, Distributed Transactions, and DBLE Insights

The fifth episode of the MySQL 冲冲冲 livestream explores the trade‑offs between sharding and middleware architectures, discusses distributed transaction challenges, compares DBLE with MyCat and other solutions, and provides practical guidance for developers and DBAs handling high‑throughput MySQL workloads.

DBLEMySQLdatabase architecture
0 likes · 19 min read
MySQL Middleware Deep Dive: Sharding vs Middleware, Distributed Transactions, and DBLE Insights
macrozheng
macrozheng
Oct 9, 2020 · Databases

How to Implement Database Sharding: Horizontal & Vertical Partitioning with Sharding-JDBC

This article explains the fundamentals of database sharding, covering both vertical and horizontal partitioning concepts, routing algorithms, advantages and drawbacks, practical implementation steps using sharding-jdbc, and discusses related challenges such as distributed transactions, pagination, global IDs, and tool selection.

JavaVertical Scalingdatabase partitioning
0 likes · 17 min read
How to Implement Database Sharding: Horizontal & Vertical Partitioning with Sharding-JDBC
Top Architect
Top Architect
Sep 12, 2020 · Backend Development

Key Considerations for Building a Generic TCC Distributed Transaction Framework

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.

SpringTCCTransactionManager
0 likes · 22 min read
Key Considerations for Building a Generic TCC Distributed Transaction Framework
Programmer DD
Programmer DD
Sep 12, 2020 · Backend Development

What’s New in Hmily? A Deep Dive into the Latest Architecture and Roadmap

The article presents Hmily’s monthly report, detailing its high‑performance distributed transaction solution, recent architectural refactoring, newly added modules and SPI implementations, community‑driven bug fixes and feature releases, and outlines upcoming versions supporting TCC and TAC modes.

Hmilybackend developmentdistributed transactions
0 likes · 6 min read
What’s New in Hmily? A Deep Dive into the Latest Architecture and Roadmap
Java Backend Technology
Java Backend Technology
Aug 30, 2020 · Databases

Mastering Database Sharding: Core Concepts, Middleware, and Common Challenges

Sharding splits a single database into multiple servers to improve performance, covering vertical and horizontal partitioning, middleware options, and key challenges such as distributed transactions, cross‑node joins, ID generation, pagination, routing transparency, and choosing between frameworks or custom solutions.

database partitioningdistributed transactionsid generation
0 likes · 16 min read
Mastering Database Sharding: Core Concepts, Middleware, and Common Challenges
21CTO
21CTO
Aug 5, 2020 · Databases

Understanding Distributed Transactions: 2PC, 3PC, Calvin, Spanner, and More

Distributed transactions require careful coordination to maintain consistency across multiple nodes, and this article explores core concepts such as atomic operations, two‑phase and three‑phase commit protocols, deterministic Calvin ordering, Google Spanner’s TrueTime and Paxos‑based approach, as well as advanced techniques like Percolator, RAMP, and coordination avoidance.

Calvin protocolRAMPSpanner
0 likes · 33 min read
Understanding Distributed Transactions: 2PC, 3PC, Calvin, Spanner, and More
Selected Java Interview Questions
Selected Java Interview Questions
Aug 5, 2020 · Backend Development

Distributed Transaction Solutions and Interview Guide

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.

TCCXAdistributed transactions
0 likes · 11 min read
Distributed Transaction Solutions and Interview Guide
Top Architect
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 theoremTCC
0 likes · 13 min read
Distributed System Characteristics and Solutions for Distributed Transaction Consistency
Alibaba Cloud Developer
Alibaba Cloud Developer
May 28, 2020 · Databases

Mastering Distributed Transactions: 5 Solutions, Patterns, and Their Trade‑offs

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.

SAGASeataTCC
0 likes · 27 min read
Mastering Distributed Transactions: 5 Solutions, Patterns, and Their Trade‑offs
Laravel Tech Community
Laravel Tech Community
May 23, 2020 · Databases

Database Sharding: Principles, Methods, and Tools

The article explains why and when to apply database sharding, describes horizontal and vertical partitioning methods, lists common sharding tools, and discusses challenges such as distributed transactions, join avoidance, pagination, and global primary key generation.

Horizontal PartitioningVertical Shardingdatabase sharding
0 likes · 14 min read
Database Sharding: Principles, Methods, and Tools
Programmer DD
Programmer DD
Apr 29, 2020 · Databases

NewSQL vs Sharding: Which Database Architecture Truly Wins?

This article objectively compares NewSQL databases with middleware‑based sharding approaches, examining their architectural differences, transaction models, CAP implications, high‑availability designs, scaling mechanisms, storage engines, maturity, and provides a decision guide to help engineers choose the right solution for their workloads.

Database ScalingNewSQLdistributed transactions
0 likes · 17 min read
NewSQL vs Sharding: Which Database Architecture Truly Wins?
Architecture Digest
Architecture Digest
Apr 25, 2020 · Backend Development

Data Consistency Strategies in Microservices: Transaction Management Patterns

This article introduces the limitations of traditional local and distributed transactions for microservices, explains the BASE theory, and details four major patterns—reliable event notification, max‑effort notification, business compensation, and TCC—to achieve eventual consistency in microservice architectures.

Data Consistencydistributed transactionseventual consistency
0 likes · 16 min read
Data Consistency Strategies in Microservices: Transaction Management Patterns
Java Backend Technology
Java Backend Technology
Apr 22, 2020 · Databases

Master MySQL Partitioning and Sharding: Theory, Practice, and Performance

This article explains the programming mindset of splitting and merging, details MySQL partition implementation and internal file types, demonstrates how partitioning improves query performance, and explores sharding strategies, middleware choices, and common issues like distributed transactions and cross‑shard joins.

MySQLPerformance Optimizationdatabase design
0 likes · 11 min read
Master MySQL Partitioning and Sharding: Theory, Practice, and Performance
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Mar 31, 2020 · Backend Development

Mastering Distributed Transactions: Reliable Messaging, TCC, and Flexible Solutions

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.

2PCBackendReliable Messaging
0 likes · 19 min read
Mastering Distributed Transactions: Reliable Messaging, TCC, and Flexible Solutions
Architects Research Society
Architects Research Society
Mar 6, 2020 · Backend Development

Ensuring Data Consistency Across Microservices: Saga, Reconciliation, Event Sourcing, and Change Data Capture

The article explains why achieving data consistency across multiple microservices is challenging, reviews the limitations of two‑phase commit, and presents practical techniques such as the Saga pattern, reconciliation, event logs, orchestration vs. choreography, and change‑data‑capture to keep distributed systems eventually consistent.

CDCData ConsistencyEvent Sourcing
0 likes · 12 min read
Ensuring Data Consistency Across Microservices: Saga, Reconciliation, Event Sourcing, and Change Data Capture
Senior Brother's Insights
Senior Brother's Insights
Jan 14, 2020 · Databases

Mastering Database Sharding: When, Why, and How to Split Your Data

This comprehensive guide explains the motivations, methods, and trade‑offs of database sharding—including vertical and horizontal partitioning, sharding rules, handling cross‑node joins, distributed transactions, global primary key generation, and practical migration strategies—so you can scale relational databases effectively.

Global ID GenerationHorizontal ShardingMySQL
0 likes · 24 min read
Mastering Database Sharding: When, Why, and How to Split Your Data
Java Architecture Diary
Java Architecture Diary
Dec 30, 2019 · Backend Development

What Is Seata? The Open‑Source Distributed Transaction Solution for Microservices

Seata is an open‑source distributed transaction framework designed for microservice architectures, offering high performance and ease of use, with origins in Alibaba’s internal consistency middleware and now commercialized, and the article outlines its AT solution alongside a comprehensive Spring Cloud Alibaba tutorial covering Nacos, Sentinel, and Seata topics.

NacosSeataSentinel
0 likes · 3 min read
What Is Seata? The Open‑Source Distributed Transaction Solution for Microservices
Programmer DD
Programmer DD
Dec 27, 2019 · Backend Development

How Perfect Diary Scaled Its E‑commerce Platform for Double‑11: Backend Lessons

During Double‑11 2022, Perfect Diary built a micro‑service e‑commerce platform in four months, confronting distributed transactions, database overload, cache pressure, and traffic spikes, and then applied cloud‑native optimizations, rate‑limiting, and pressure testing to achieve record‑breaking sales performance.

Cloud ComputingPerformance Optimizationdistributed transactions
0 likes · 9 min read
How Perfect Diary Scaled Its E‑commerce Platform for Double‑11: Backend Lessons
Programmer DD
Programmer DD
Dec 12, 2019 · Databases

Mastering Data Sharding: When and How to Split Your Database for Scale

This article explains the concepts, benefits, and challenges of database sharding—including vertical and horizontal partitioning, common splitting strategies, handling distributed transactions, cross‑node joins, pagination, global primary keys, and migration—while offering practical guidelines on when to adopt sharding and which tools can assist.

Horizontal PartitioningVertical Partitioningdatabase sharding
0 likes · 26 min read
Mastering Data Sharding: When and How to Split Your Database for Scale
dbaplus Community
dbaplus Community
Nov 3, 2019 · Databases

Insights from Data Platform Experts: Distributed Transactions, Aurora, and HBase

A recent data platform salon in Beijing gathered five leading experts who shared practical knowledge on data middle platforms, distributed transaction patterns, SQL audit design, Amazon Aurora's architecture, and JD's large‑scale HBase deployment, offering actionable guidance for modern enterprise data engineering.

HBaseSQL auditcloud databases
0 likes · 6 min read
Insights from Data Platform Experts: Distributed Transactions, Aurora, and HBase
Java High-Performance Architecture
Java High-Performance Architecture
Nov 1, 2019 · Backend Development

Mastering Seata: A Deep Dive into Distributed Transaction Management

This article explains Seata’s architecture, core components, and step‑by‑step AT mode workflow—including transaction initiation, branch handling, undo‑log mechanisms, and two‑phase commit/rollback—providing a practical guide for implementing reliable distributed transactions in microservice systems.

AT ModeSeatadistributed transactions
0 likes · 9 min read
Mastering Seata: A Deep Dive into Distributed Transaction Management
ITPUB
ITPUB
Oct 24, 2019 · Databases

How JDTX Achieves High‑Performance Distributed Transactions with MVCC and WAL

This article explains the design and implementation of JDTX, a distributed transaction middleware that combines MVCC, WAL, and a one‑phase commit model to provide strong ACID guarantees, high performance, and multi‑database support while outlining its challenges and future roadmap.

Database MiddlewareJDTXMVCC
0 likes · 17 min read
How JDTX Achieves High‑Performance Distributed Transactions with MVCC and WAL
JD Tech Talk
JD Tech Talk
Oct 24, 2019 · Databases

JDTX Distributed Transaction Solution: Design Principles, Features, and Implementation Challenges

This article introduces JDTX, a high‑performance, ACID‑compliant distributed transaction middleware, explains its architecture based on WAL and MVCC, compares rigid two‑phase commit and flexible BASE‑based approaches, and discusses the technical difficulties and future roadmap for integrating JDTX with Apache ShardingSphere and cloud‑native platforms.

ACIDDatabase MiddlewareJDTX
0 likes · 15 min read
JDTX Distributed Transaction Solution: Design Principles, Features, and Implementation Challenges
Programmer DD
Programmer DD
Aug 16, 2019 · Backend Development

Designing a Scalable Microservice E‑Commerce System with DDD, Distributed Transactions, and Resilience

This article walks through the complete design of an e‑commerce microservice architecture, covering module identification, domain‑driven design, service splitting, technology stack choices between Dubbo and Spring Cloud, distributed transaction patterns, resilience with Hystrix, centralized configuration, and observability with SkyWalking.

DDDHystrixSpring Cloud
0 likes · 27 min read
Designing a Scalable Microservice E‑Commerce System with DDD, Distributed Transactions, and Resilience
Aikesheng Open Source Community
Aikesheng Open Source Community
Aug 12, 2019 · Databases

Choosing Between NewSQL Databases and Middleware‑Based Sharding: A Comparative Analysis

This article objectively compares NewSQL distributed databases with middleware‑based sharding solutions, examining their architectures, distributed transaction handling, scalability, performance, high‑availability, and operational considerations, and provides guidance on selecting the appropriate approach based on workload, consistency, and organizational constraints.

CAP theoremNewSQLdistributed databases
0 likes · 19 min read
Choosing Between NewSQL Databases and Middleware‑Based Sharding: A Comparative Analysis
AntTech
AntTech
Jul 29, 2019 · Backend Development

Ant Financial’s Distributed Transaction Evolution and the Open‑Source Seata Framework

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.

AT ModeSAGASeata
0 likes · 15 min read
Ant Financial’s Distributed Transaction Evolution and the Open‑Source Seata Framework
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-SQLDatabase OptimizationLatch
0 likes · 13 min read
Optimizing Distributed Transactions in CB‑SQL: From Two‑Phase Commit to Parallel and Pipeline Commit
Aikesheng Open Source Community
Aikesheng Open Source Community
May 29, 2019 · Databases

DBLE XA Transaction Implementation and Recovery Analysis

This article provides a comprehensive analysis of DBLE's XA transaction implementation, covering XA protocol basics, DBLE's architecture, code structure, execution flow, error handling, transaction logging, recovery mechanisms, and practical considerations for distributed transactions in database middleware.

DBLEMySQLTransaction Recovery
0 likes · 25 min read
DBLE XA Transaction Implementation and Recovery Analysis
Java High-Performance Architecture
Java High-Performance Architecture
May 15, 2019 · Databases

How to Achieve Distributed Transaction Consistency with Message Queues

This article explains how to handle distributed transactions in microservice architectures by using eventual consistency with message middleware, discusses the pitfalls of combining database updates and message sending in a single transaction, and presents a reliable solution involving a message table, background processing, ACK mechanisms, and deduplication.

distributed transactionseventual consistencyidempotency
0 likes · 5 min read
How to Achieve Distributed Transaction Consistency with Message Queues
AntTech
AntTech
Apr 29, 2019 · Backend Development

Interview with Lu Zhi on SOFA5, Service Mesh, Seata and Open‑Source Practices at Ant Financial

In this interview, Lu Zhi, the technical lead of Ant Financial's SOFA middleware, discusses the evolution from SOFA4 to SOFA5, the strategic importance of Service Mesh and Serverless, the development of the Seata distributed‑transaction framework, and the team’s open‑source governance and community‑building approaches.

Cloud ComputingSOFASeata
0 likes · 15 min read
Interview with Lu Zhi on SOFA5, Service Mesh, Seata and Open‑Source Practices at Ant Financial
Architecture Digest
Architecture Digest
Apr 1, 2019 · Backend Development

Seven Reliable Methods for Solving Distributed Transaction Problems

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.

2PCTCCdistributed transactions
0 likes · 25 min read
Seven Reliable Methods for Solving Distributed Transaction Problems
JD Tech
JD Tech
Mar 7, 2019 · Databases

Distributed Transaction Solutions in Apache ShardingSphere: XA, Saga, and Flexible Transactions

Apache ShardingSphere provides an integrated distributed transaction solution combining traditional ACID‑compliant two‑phase commit, flexible Saga‑based transactions, and automatic transaction management, detailing their architectures, features, trade‑offs, and usage guidelines for developers handling multi‑database microservice environments.

SAGAShardingSphereXA
0 likes · 18 min read
Distributed Transaction Solutions in Apache ShardingSphere: XA, Saga, and Flexible Transactions
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 storeRaftReplication
0 likes · 15 min read
How Do Fault‑Tolerant Transactions Work? Exploring Raft, KV Engines, and Concurrency Control
Alibaba Cloud Developer
Alibaba Cloud Developer
Jan 25, 2019 · Fundamentals

How Alibaba’s Fescar Tackles Distributed Transactions in Microservices

This article explains the distributed‑transaction challenges introduced by microservice architectures, introduces Alibaba’s open‑source Fescar (formerly GTS) as a non‑intrusive, high‑performance solution, and details its design principles, components, AT/MT modes, extension points, and roadmap for future development.

AT ModeFescarJava
0 likes · 22 min read
How Alibaba’s Fescar Tackles Distributed Transactions in Microservices
Programmer DD
Programmer DD
Jan 15, 2019 · Backend Development

Mastering RocketMQ Transactional Messages for Distributed Consistency

This article explains how RocketMQ’s transactional message feature enables distributed transaction final consistency by using half messages, message check‑back, and defined transaction states, and provides complete Java code samples for producers, listeners, and consumer idempotency handling.

JavaRocketMQTransactional Messaging
0 likes · 10 min read
Mastering RocketMQ Transactional Messages for Distributed Consistency
Java Captain
Java Captain
Jan 12, 2019 · Backend Development

An Overview of Alibaba’s Open‑Source Distributed Transaction Framework Fescar (Seata)

Fescar, Alibaba’s open‑source Fast & Easy Commit And Rollback (Seata) framework, provides a high‑performance, easy‑to‑use distributed transaction solution for microservice architectures, detailing its components, transaction lifecycle, and evolution from TXC to GTS, and illustrating its role in solving global transaction challenges.

AlibabaFescarSeata
0 likes · 5 min read
An Overview of Alibaba’s Open‑Source Distributed Transaction Framework Fescar (Seata)
Java Backend Technology
Java Backend Technology
Jan 11, 2019 · Backend Development

How Fescar Simplifies Distributed Transactions in Microservices

This article introduces Fescar, Alibaba's open‑source distributed transaction framework for microservices, explains the challenges of global transactions, outlines its architecture and components, and reviews its evolution from TXC to GTS to Fescar.

AlibabaFescardistributed transactions
0 likes · 5 min read
How Fescar Simplifies Distributed Transactions in Microservices
Programmer DD
Programmer DD
Jan 8, 2019 · Backend Development

How to Build a Reliable Message Service for Distributed Transactions

This article explains how to design and implement a reliable message service that ensures atomicity between upstream business transactions and downstream message delivery, using status management, callbacks, and scheduled tasks to achieve eventual consistency in distributed systems.

Reliable Messagingdistributed transactionseventual consistency
0 likes · 9 min read
How to Build a Reliable Message Service for Distributed Transactions
Programmer DD
Programmer DD
Dec 26, 2018 · Backend Development

How Maximum‑Effort Notification Solves Distributed Transaction Challenges

This article explains the Maximum‑Effort Notification pattern for flexible distributed transactions, detailing its principles, workflow, implementation options, evaluation, and optimization techniques to achieve eventual consistency across services with limited retries and idempotent interfaces.

distributed transactionseventual consistencymaximum effort
0 likes · 11 min read
How Maximum‑Effort Notification Solves Distributed Transaction Challenges
Java Architect Essentials
Java Architect Essentials
Oct 30, 2018 · Backend Development

Understanding Distributed Transactions: Theory, Models, and .NET Solutions

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.

2PCBackendCAP theorem
0 likes · 15 min read
Understanding Distributed Transactions: Theory, Models, and .NET Solutions
Big Data and Microservices
Big Data and Microservices
Sep 20, 2018 · Backend Development

Why Distributed Transactions Matter: Concepts, Scenarios, and Solutions

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.

2PCTCCXA protocol
0 likes · 12 min read
Why Distributed Transactions Matter: Concepts, Scenarios, and Solutions
Architects' Tech Alliance
Architects' Tech Alliance
Sep 11, 2018 · Databases

Understanding Distributed Transactions: Principles, 2PC, 3PC, XA, Saga, and Message‑Based Approaches

This article explains the fundamentals of database transactions, the ACID properties, and how they are implemented, then delves into distributed transaction challenges and solutions such as two‑phase and three‑phase commit, XA, Saga patterns, choreography vs. orchestration, and message‑based transaction mechanisms.

2PC3PCACID
0 likes · 16 min read
Understanding Distributed Transactions: Principles, 2PC, 3PC, XA, Saga, and Message‑Based Approaches
Java Backend Technology
Java Backend Technology
Jul 15, 2018 · Backend Development

Mastering TCC: Key Design Practices for Reliable Distributed Transactions

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.

TCCdistributed transactionstransaction management
0 likes · 6 min read
Mastering TCC: Key Design Practices for Reliable Distributed Transactions
ITPUB
ITPUB
May 28, 2018 · Databases

Mastering Database Sharding: When and How to Split Your Data

This article explains why and how relational databases should be sharded, covering vertical and horizontal partitioning techniques, common pitfalls such as distributed transactions and join queries, and practical guidelines for deciding when to split data and which tools to use.

Horizontal PartitioningVertical Partitioningdistributed transactions
0 likes · 22 min read
Mastering Database Sharding: When and How to Split Your Data
ITPUB
ITPUB
May 24, 2018 · Databases

How Ant Financial Solved Distributed Transaction Challenges with TCC, FMT, and XA

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.

TCCXAdatabase consistency
0 likes · 20 min read
How Ant Financial Solved Distributed Transaction Challenges with TCC, FMT, and XA
Architecture Digest
Architecture Digest
May 20, 2018 · Backend Development

Understanding Distributed Transactions and the XA Two‑Phase Commit Protocol

The article explains how distributed transactions work in microservice architectures, using inventory‑order examples and a World of Warcraft raid analogy to illustrate the XA two‑phase commit protocol, its normal and failure flows, limitations, and alternative approaches such as three‑phase commit, message‑queue and TCC transactions.

XA protocolconsistencydistributed transactions
0 likes · 7 min read
Understanding Distributed Transactions and the XA Two‑Phase Commit Protocol
Beike Product & Technology
Beike Product & Technology
May 4, 2018 · Backend Development

QCon Technical Sharing: Alibaba Pandora Microservice Framework, 51 Credit Card Monitoring Platform, JD Akimed Service Platform, and Saga Distributed Transaction Solutions

The article summarizes four technical sessions from QCon covering Alibaba's Pandora microservice isolation framework and its boot solution, 51 Credit Card's monitoring platform design, JD's Akimed service platform with ContainerMesh and capability mapping, and a saga‑based distributed transaction library, highlighting challenges, implementations, and practical insights.

BackendPandoraSAGA
0 likes · 11 min read
QCon Technical Sharing: Alibaba Pandora Microservice Framework, 51 Credit Card Monitoring Platform, JD Akimed Service Platform, and Saga Distributed Transaction Solutions
Java Backend Technology
Java Backend Technology
Mar 19, 2018 · Fundamentals

Why Distributed Consistency Matters: From CAP to BASE Explained

This article explores the importance of data consistency in distributed systems, illustrating real‑world scenarios, explaining consistency models such as strong, weak and eventual, and detailing the challenges and theories like CAP and BASE that guide system designers in balancing consistency, availability, and partition tolerance.

BASE theoryCAP theoremconsistency
0 likes · 18 min read
Why Distributed Consistency Matters: From CAP to BASE Explained
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 9, 2018 · Backend Development

Why Distributed Transactions Stall Microservices and How Alibaba’s GTS Solves It

The article examines the challenges of distributed transactions in microservice architectures, reviews traditional solutions such as XA, TCC, and message-based eventual consistency, and introduces Alibaba’s Global Transaction Service (GTS) as a high‑performance, low‑intrusion middleware with various deployment options and real‑world usage examples.

GTSdistributed transactions
0 likes · 19 min read
Why Distributed Transactions Stall Microservices and How Alibaba’s GTS Solves It
Zhuanzhuan Tech
Zhuanzhuan Tech
Oct 31, 2017 · Cloud Native

Key Technologies and Design Patterns for Implementing Microservices: Architecture Characteristics, Patterns, and Data Consistency

This article explains microservice architecture fundamentals, typical design patterns such as chain, aggregator, data‑sharing and asynchronous messaging, and presents practical solutions for service splitting, data consistency, and distributed transaction management based on real‑world experience at the ZhaiZhai platform.

Data ConsistencyDesign Patternsarchitecture
0 likes · 9 min read
Key Technologies and Design Patterns for Implementing Microservices: Architecture Characteristics, Patterns, and Data Consistency
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Oct 3, 2017 · Backend Development

Why Distributed Transactions Still Matter: Strategies Beyond 2PC

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.

2PCBASECAP theorem
0 likes · 11 min read
Why Distributed Transactions Still Matter: Strategies Beyond 2PC
21CTO
21CTO
Sep 29, 2017 · Databases

Ensuring Distributed Consistency: From Local Transactions to Two‑Phase Commit

The article examines how to achieve data consistency in distributed internet systems by comparing strong and eventual consistency, detailing local database transactions, two‑phase commit protocols, rollback mechanisms, local message tables, and compensation strategies, and discusses their trade‑offs and suitable application scenarios.

compensationdistributed transactionslocal message table
0 likes · 11 min read
Ensuring Distributed Consistency: From Local Transactions to Two‑Phase Commit
Architecture Digest
Architecture Digest
Sep 10, 2017 · Backend Development

Understanding Distributed Transaction Patterns: TCC, Asynchronous Assurance, and Maximum Effort Notification

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.

TCCasynchronous assurancebackend development
0 likes · 4 min read
Understanding Distributed Transaction Patterns: TCC, Asynchronous Assurance, and Maximum Effort Notification
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Jul 28, 2017 · Databases

Sharding Mastery: Strategies, Key Generation & Seamless Scaling

This article presents a comprehensive guide to database sharding, covering implementation strategies, vertical and horizontal partitioning, global primary key generation techniques, framework versus custom solutions, multi‑data‑source transaction handling, and a novel, migration‑free scaling approach that combines incremental range and hash‑based routing.

Database ScalingPrimary Key Generationbackend development
0 likes · 31 min read
Sharding Mastery: Strategies, Key Generation & Seamless Scaling
dbaplus Community
dbaplus Community
Jul 27, 2017 · Databases

How Sharding-JDBC Transforms Relational Databases for Scalable Cloud‑Native Applications

This article explains the core functions of relational‑database middleware, dives into Sharding-JDBC’s architecture, performance characteristics, and implementation details such as sharding rules, SQL parsing, routing, rewrite, execution, result merging, and distributed primary‑key generation, and outlines its future roadmap.

Database MiddlewareJavaSQL Routing
0 likes · 21 min read
How Sharding-JDBC Transforms Relational Databases for Scalable Cloud‑Native Applications
Architecture Digest
Architecture Digest
May 31, 2017 · Operations

Designing Distributed Transaction Architecture and Ensuring Data Consistency in a Flow Recharge System

The article explains how to break large transactions into small atomic operations combined with asynchronous messaging, describes ACID properties, presents banking and flow‑recharge scenarios, compares local and distributed (flexible) transactions, and details micro‑service architecture, compensation and async strategies to achieve eventual consistency.

Data Consistencyasynchronous notificationcompensation
0 likes · 11 min read
Designing Distributed Transaction Architecture and Ensuring Data Consistency in a Flow Recharge System
21CTO
21CTO
Apr 15, 2017 · Backend Development

How to Design Distributed Transactions for Consistent Microservices

This article explains the principles of distributed transaction design, covering ACID fundamentals, typical banking and e‑commerce scenarios, various transaction models such as two‑phase, compensation, asynchronous and best‑effort notifications, and presents a micro‑service architecture with concrete flow diagrams and scaling strategies for a high‑throughput traffic‑recharge platform.

Data Consistencydistributed transactionseventual consistency
0 likes · 12 min read
How to Design Distributed Transactions for Consistent Microservices
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Apr 7, 2017 · Databases

Mastering Final Consistency: Strategies for Distributed Transactions

Ensuring final data consistency in modern applications—whether enterprise or internet—requires understanding ACID, CAP, BASE theories and applying practical techniques such as single-database transactions, two-phase commit, transactional message queues, compensation tasks, async callbacks, and double-check mechanisms to build robust distributed systems.

ACIDBASECAP
0 likes · 8 min read
Mastering Final Consistency: Strategies for Distributed Transactions
Architecture Digest
Architecture Digest
Nov 8, 2016 · Backend Development

Why Replace Distributed Transactions? A Message Queue and State‑Table Solution

The article explains the drawbacks of traditional two‑phase commit distributed transactions—reduced availability, performance, and scalability—and proposes a message‑queue‑plus‑state‑table pattern with idempotent processing to achieve eventual consistency while improving system throughput.

backend architecturedatabase consistencydistributed transactions
0 likes · 7 min read
Why Replace Distributed Transactions? A Message Queue and State‑Table Solution
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Nov 4, 2016 · Databases

Mastering Sharding: Strategies, Key Generation, and Seamless Scaling

This article explains practical sharding implementation strategies, global primary‑key generation techniques, framework versus custom solutions, distributed transaction models, and a flexible expansion scheme that avoids data migration while maintaining performance and scalability.

Database ScalingPrimary Key Generationdistributed transactions
0 likes · 31 min read
Mastering Sharding: Strategies, Key Generation, and Seamless Scaling
Nightwalker Tech
Nightwalker Tech
Sep 8, 2016 · Backend Development

Technical Discussion on Distributed Transactions, RPC Frameworks, Session Security, and Messaging Solutions

The conversation covers practical challenges and solutions for distributed transactions, evaluates RPC frameworks like Thrift, Dubbo, and gRPC, discusses session replay attack mitigations, and explores reliable messaging patterns using queues and pub/sub systems such as RabbitMQ and Kafka.

RPC frameworksSession Securitydistributed transactions
0 likes · 10 min read
Technical Discussion on Distributed Transactions, RPC Frameworks, Session Security, and Messaging Solutions
High Availability Architecture
High Availability Architecture
Aug 11, 2016 · Backend Development

Mogujie E‑Commerce Transaction Platform Architecture and Service Refactoring

The article details how Mogujie's e‑commerce transaction system evolved from a monolithic PHP application to a service‑oriented architecture through DB vertical sharding, service decomposition, custom sharding component TSharding, and performance optimizations such as asynchronous processing, caching, and distributed transaction handling to support rapid growth and high‑availability requirements.

Backenddistributed transactionse-commerce
0 likes · 15 min read
Mogujie E‑Commerce Transaction Platform Architecture and Service Refactoring
dbaplus Community
dbaplus Community
May 20, 2016 · Databases

Inside TiKV: MVCC Mechanics and Distributed Transaction Design

This article explains how TiKV implements multi-version concurrency control (MVCC) on top of RocksDB and details its two‑phase commit transaction model, including Prewrite and Commit phases, Percolator‑style optimizations, lock handling, conflict resolution, and garbage‑collection strategies.

Garbage CollectionMVCCPercolator
0 likes · 14 min read
Inside TiKV: MVCC Mechanics and Distributed Transaction Design
Qunar Tech Salon
Qunar Tech Salon
Apr 26, 2016 · Databases

Distributed Transaction and Data Consistency Solutions for E‑commerce Systems

The article examines the challenges of maintaining data consistency across distributed services in e‑commerce, explains strong, weak and eventual consistency models, and presents six practical solutions—including business integration, the eBay BASE pattern, Qunar, Mogujie, Alipay DTS, and Nongxin—highlighting how local transactions, idempotent messaging, and eventual consistency can replace heavyweight distributed‑transaction frameworks.

BASEData Consistencydistributed transactions
0 likes · 16 min read
Distributed Transaction and Data Consistency Solutions for E‑commerce Systems
Architecture Digest
Architecture Digest
Apr 4, 2016 · Backend Development

Handling Distributed Transactions in Large‑Scale Microservice Systems

The article examines the challenges of distributed transactions in large‑scale microservice architectures and compares three main approaches—traditional two‑phase commit, stateless queue‑based eventual consistency with event sourcing and CQRS, and transaction compensation techniques such as TCC—highlighting their trade‑offs and real‑world examples like Flipkart.

CQRSEvent Sourcingdistributed transactions
0 likes · 8 min read
Handling Distributed Transactions in Large‑Scale Microservice Systems
MaGe Linux Operations
MaGe Linux Operations
Feb 4, 2016 · Databases

Mastering Database Sharding: Vertical & Horizontal Partitioning Strategies

This article explains the core concepts of database sharding, detailing vertical and horizontal partitioning methods, strategies for combining them, handling shared data, and addressing challenges such as distributed transactions, cross‑node joins, and aggregation queries, with practical insights for scalable system design.

Horizontal ShardingVertical Shardingcross-node queries
0 likes · 9 min read
Mastering Database Sharding: Vertical & Horizontal Partitioning Strategies