This article explains the fundamentals of distributed transactions, including ACID properties, consistency models, sharding strategies, and the two‑phase, three‑phase, and TCC protocols, while discussing CAP and BASE theories and the challenges of implementing reliable distributed databases.
This article explains the fundamentals of distributed transactions, the ACID properties, various consistency models, database sharding strategies, and the two‑phase, three‑phase, and TCC commit protocols, while also discussing CAP, BASE, and practical challenges in large‑scale systems.
This article explains the fundamentals of distributed transactions, covering ACID properties, consistency models, sharding strategies, CAP and BASE theories, and compares two‑phase, three‑phase, and TCC commit protocols to illustrate how modern systems maintain data integrity across multiple nodes.
This article explains rigid (strong consistency) distributed transactions, detailing the XA protocol and the classic two‑phase commit (2PC) and three‑phase commit (3PC) mechanisms, their workflows, advantages, limitations, and practical considerations for database systems.
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.
This article explains the fundamentals of distributed consistency, covering the CAP theorem, BASE model, two‑phase and three‑phase commit protocols, Paxos and Raft consensus algorithms, Zookeeper’s ZAB protocol, and Amazon Dynamo’s NWR model with vector clocks for conflict resolution.
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 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 introduces core distributed‑system concepts—including the definition of consensus, the two‑phase and three‑phase commit protocols, the CAP theorem and its engineering implications, and logical‑clock mechanisms such as Lamport timestamps, vector clocks, and version vectors—explaining their models, challenges, and practical trade‑offs.
