This article explains the fundamentals of database sharding and partitioning, why they are needed for massive data volumes, various vertical and horizontal splitting strategies, routing algorithms, client vs. proxy deployment models, and the practical challenges and solutions when using ShardingSphere 5.x.
This article explains why database sharding is needed, the problems caused by oversized databases and tables, and how to apply vertical and horizontal splitting using MyCat, including configuration examples, splitting strategies, and testing procedures.
This article explains why and when to apply database sharding, distinguishes between sharding databases, tables, or both, describes horizontal and vertical splitting, guides key selection and sharding algorithms, covers global ID generation, lists open‑source tools, and discusses the operational challenges introduced by sharding.
This article explains vertical and horizontal database sharding, compares hash‑modulo and range‑based partitioning schemes, and discusses their advantages, drawbacks, and the impact on scaling and hotspot problems in large‑scale applications.
The article examines how the rapid growth of mobile and aggregated payments strains traditional IOE‑based payment systems, and outlines a comprehensive distributed transformation strategy that includes vertical service‑oriented splitting, horizontal sharding by data type, and practical approaches to handling distributed transactions, cross‑shard queries, scaling, disaster recovery, and operational monitoring.
This article explains how a massive order database exceeding 200 GB was vertically and horizontally sharded, introduces query, range, and hash sharding strategies, presents a custom timestamp‑based unique ID scheme, and outlines a multi‑phase data migration plan to achieve long‑term scalability.
The article explains the concepts of vertical and horizontal database splitting, compares their technical difficulties, discusses the impact on joins and transactions, and proposes practical approaches such as careful SQL refactoring, ORM decoupling, and selective use of distributed‑transaction techniques to maintain system stability and scalability.
