This article provides a detailed tutorial on database sharding (分库分表), covering concepts, common sharding strategies, a step‑by‑step MyCAT configuration, Java JDBC implementation, and key considerations such as data distribution, complexity, transaction handling, and development cost.
The article details a real‑world case study of building and operating a high‑traffic business middle‑platform for a leading consumer‑goods company, covering business and technical architecture, API gateway selection, SpringBoot microservices, custom MyBatis, logging, SSL, Docker, MyCat sharding, K8s deployment, CI/CD pipeline, and monitoring solutions.
This article explains the difference between database sharding and table partitioning, illustrates scaling challenges with a fast‑growing startup scenario, and compares popular sharding middleware such as Cobar, TDDL, Atlas, ShardingSphere, and Mycat, offering practical recommendations for different company sizes.
This article introduces database middleware, explains why it’s needed for scaling and performance, and provides a detailed overview of six popular middleware solutions—including ShardingSphere, MyCat, MySQL‑Proxy, DRDS, Atlas, and Zebra—highlighting their core features and use cases.
This article explains what database middleware is, why it’s needed for scaling large data workloads, and provides detailed overviews of six popular middleware solutions—including MyCat, MySQL‑Proxy, DRDS, Atlas, Zebra, and ShardingSphere—highlighting their key features and use cases.
This article examines the storage challenges faced by large‑scale internet services and evaluates popular MySQL middleware solutions—ProxySQL, MaxScale, DBProxy, MyCat, and TDDL—by mapping business requirements to their core features and capabilities.
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.
The SQLE 2.2306.0-pre1 release introduces support for TDSQL InnoDB and Mycat data sources in enterprise edition, adds new features, UI optimizations, bug fixes, and provides detailed usage instructions and links to documentation, source code, and demo environments.
This article details a low‑impact migration from MyCat to DBLE, covering required parameter adjustments, sharding function replacement, data node handling, and business‑SQL compatibility issues, while providing concrete configuration examples and practical recommendations for a smooth transition.
This article explains why high‑traffic systems need database sharding, compares table‑level and database‑level partitioning methods, presents concrete MySQL table‑creation scripts and Java service code, and discusses the advantages, drawbacks, and common middleware solutions such as Sharding‑JDBC and Mycat.
This guide explains the concepts, benefits, and step‑by‑step configuration of MySQL master‑slave replication and read/write splitting, including required master and slave settings, practical VM setup, and Mycat configuration files for routing reads and writes.
This article explains what database sharding (horizontal and vertical partitioning) is, why it is needed, the implementation strategies, and compares two popular solutions—Mycat middleware and Sharding-JDBC—highlighting their advantages, drawbacks, and typical use cases.
This tutorial explains how to set up MySQL master‑slave replication, configure MyCat as a database middleware, install and configure MyCat, and integrate it with a SpringBoot application using dynamic data sources and AOP to achieve transparent read‑write separation.
This guide walks through installing MySQL nodes, Java, and MyCat 1.6.5, configuring schemas, data nodes, sharding rules, adjusting ports, adding users, and verifying the MyCat service, providing complete code snippets and troubleshooting tips for a functional distributed database middleware setup.
This tutorial explains two approaches to achieve MySQL read/write splitting—first by manually implementing routing logic in Spring Boot with MyBatis interceptors and dynamic data sources, and second by configuring the MyCat middleware for automatic load balancing, fault‑tolerance, and multi‑node support, complete with code samples and configuration files.
This article analyzes a community‑raised issue where a left join between a global table and a sharded table produces incorrect results in Mycat but works as expected in DBLE, explaining the underlying execution‑plan differences and how DBLE correctly merges results to avoid duplicate data.
The iKesheng community’s weekly roundup shares upcoming events like the DBLE Beijing meet‑up, free Mycat diagnosis services, detailed DBLE and DTLE weekly reports, and technical articles on global lock detection, slave data search, and hash algorithm choices, offering valuable insights for database professionals.
This article provides a concise, ten‑minute guide to MySQL master‑slave and master‑master replication, data sharding principles and implementations, and various database deployment architectures—including single‑instance, replication‑based scaling, and sharding‑based scaling—while highlighting practical considerations, advantages, and common pitfalls.
This article explains DBLE's hash‑based sharding algorithm that first computes a modulo to obtain a logical shard number and then directly maps it to a physical shard via a mapping table derived from partitionLength and partitionCount arrays, including configuration steps, development tips, operational guidance, and a comparison with MyCat.
This article presents a step‑by‑step comparison of DBLE and Mycat distributed middleware by setting up a test environment, defining table schemas and sharding rules, inserting sample data, executing the same cross‑node join query on both systems, and analyzing the differing results and execution plans to explain why Mycat omits expected rows while DBLE returns the correct result.
The article examines MyCat’s middleware‑based pseudo‑distributed MySQL architecture, outlines its storage, scalability, and reliability shortcomings, walks through common solutions like disk expansion, compression, and sharding, and finally offers practical steps and alternative technologies for building truly distributed database systems.
This article explains the core concepts of distributed architecture, including cohesion and transparency, explores common applications such as distributed file systems, caches, databases, and middleware like MyCat, and outlines the evolutionary stages and challenges of building scalable distributed systems.
This talk details SF Express’s journey from heterogeneous legacy databases to standardized open‑source, distributed architectures and intelligent operations, covering standardization, migration to open‑source, scaling with Mycat, automated resource pooling, and the ThinkDB platform that drives proactive, automated DBA workflows.
This article explains MyCat's role as a database middleware, tracing the evolution from single‑database setups through distributed deployment, caching, master‑slave, vertical and horizontal sharding, and shows how MyCat automates data‑source and shard selection to reduce code complexity.
The article explains the concept of distributed architecture, its key characteristics such as cohesion and transparency, showcases how MySQL and middleware like Mycat are used in e‑commerce platforms, and outlines the evolution, practical implementations, and challenges of building scalable distributed database systems.
This guide walks you through downloading MyCat, setting up the MySQL environment, configuring server.xml, schema.xml, and rule.xml for sharding, and starting MyCat on Windows, including connection details and sample c3p0 pool configuration, with screenshots for each step.
This tutorial walks through setting up a Mycat environment, creating required databases and users, installing JDK7 and Mycat, configuring environment variables and MySQL settings, defining sharding rules, and verifying both read/write separation and automatic failover in a master‑slave MySQL cluster.
The article introduces MyCat, an open‑source distributed database middleware that provides transparent sharding, multi‑backend support, AI‑driven catlet extensions, and advanced read‑write splitting to enable low‑cost migration of single‑node databases to cloud environments while addressing performance and scalability challenges.
MyCat is an open‑source distributed database middleware that transparently shreds tables across multiple backend databases, solves connection overload, provides ER‑based sharding, global partitioning, AI‑driven catlets, and advanced read‑write separation, enabling low‑cost migration of single‑node databases to the cloud.
