The article revisits the CAP theorem, explains why the classic "two‑of‑three" interpretation is misleading, compares ACID, BASE and CAP, discusses the role of latency, and presents practical strategies for detecting, handling, and recovering from network partitions in distributed systems.
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 how data consistency is achieved through local ACID transactions, global XA/2PC mechanisms, CAP and BASE theories, and practical patterns such as reliable events, TCC, and SAGA, providing a comprehensive overview for architects designing distributed systems.
This article explains the concept of database transactions, the ACID properties, how MySQL implements transactions with InnoDB, how to manage autocommit, the essential transaction control statements, a practical example using savepoints, and the four isolation levels supported by MySQL.
OceanBase’s TPC‑C benchmark demonstrates how its distributed database achieves high durability, atomicity, isolation, and consistency on commodity cloud servers using Paxos‑based log replication, two‑phase commit, MVCC, and replicated tables, highlighting the architectural challenges and solutions for ACID compliance.
This article explains the fundamentals of database transactions, the ACID properties, how they differ in distributed environments, and details two‑phase and three‑phase commit protocols while offering personal insights on the challenges of implementing distributed transactions.
This article explains how MySQL implements transaction ACID properties by using redo and undo logs, lock mechanisms, and MVCC, detailing the roles of each component in achieving atomicity, durability, isolation, and consistency for reliable concurrent data processing.
This article explains the fundamentals of local transactions and ACID properties, introduces CAP and BASE theories, discusses compensation jobs and transaction messages, and reviews distributed transaction models such as two‑phase commit, three‑phase commit, XA, TCC, Saga, and the Seata framework.
This article explains how MySQL implements transaction features such as atomicity, durability, and isolation by using redo logs, undo logs, lock mechanisms, and MVCC, detailing their roles, generation processes, and the impact of different isolation levels on data consistency.
The article explains distributed consistency problems and the two‑phase commit (2PC) protocol using a restaurant kitchen and a multiplayer game analogy, detailing how a coordinator ensures atomic transactions across multiple services and discussing the inherent drawbacks of 2PC.
This article explains the fundamentals of database transactions, the ACID properties, implementation details such as transaction logs and concurrency control, and explores distributed transaction solutions including two‑phase and three‑phase commit, XA, Saga patterns, 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 explains how MySQL InnoDB guarantees the ACID properties—Atomicity, Consistency, Isolation, and Durability—through its lock mechanisms, multi‑version concurrency control, undo/redo logs, buffer pool management, and the interaction between binlog and redo log.
This article explains the fundamentals of ACID, how Redis implements transactions with MULTI, EXEC, DISCARD and WATCH commands, provides code examples, and analyzes whether Redis transactions satisfy atomicity, consistency, isolation, and durability.
This article explains the concept of database transactions, the ACID properties, various isolation levels, and how Spring Framework implements transaction propagation, isolation, and architecture, providing both theoretical background and practical guidance for developers.
This article explains the core concepts of database transactions—including ACID properties, common concurrency anomalies, MySQL isolation levels, Spring's isolation and propagation settings, and the CAP theorem's impact on distributed transactions—providing a comprehensive overview for developers and engineers.
This article introduces JD's real‑time data warehouse evolution, outlines the limitations of traditional Lambda‑based warehouses, compares open‑source lake formats (Delta, Hudi, Iceberg), explains Delta Lake's transaction‑log architecture and read flow, and demonstrates how a unified batch‑stream development model simplifies data processing and improves reliability.
This article provides a comprehensive overview of MySQL InnoDB's internal architecture, covering its memory and disk structures, buffer pool, change buffer, adaptive hash index, log buffer, various tablespace types, page layout, undo and redo logs, double‑write buffer, transaction isolation levels, and how the engine satisfies ACID properties.
This article explains the concept of database transactions, their ACID properties, and provides a step‑by‑step Node.js example using the Bookshelf.js ORM to safely perform multi‑table operations within a transaction.