ShardingSphere is positioned as a Database Plus, and aims at building a new criterion and ecosystem above multi‐model databases. It focuses on how to reuse existing databases and their re‐ spective upper layer adaptation of database protocol, SQL dialect and database storage. It can quickly link applications and multi‐mode heterogeneous databases quickly. • Enhance: Capture database access entry to provide additional Distributed Database* Data Security Database Gateway Stress T esting Data Sharding Data Encrypt Multi‐model Databases Sup‐ ported Shadow D atabase Readwrit e‐ splitting Row Authority (TODO) SQL

they are binding tables with each other. Carte‐ sian product correlation will not appear in the multi‐table correlating query, so the query efficiency will increase greatly. Take this one for example database, and can be divided into correctness rewrite and optimization rewrite. SQL Execution Through multi‐thread executor, it executes asynchronously. Result Merger It merges multiple execution result sets efficiency, holding an independent database connection for each sharding query can make effective use of multi‐thread to improve execution efficiency. Opening an independent thread for each database connection

architecture, features can be flexibly expanded at will. The project is committed to providing a multi‐source heterogeneous, enhanced database platform and further building an ecosystem around the upper needs. • Open Ecosystem It can provide users with flexibility thanks to custom systems based on multi‐level (kernel, feature, and ecosystem) plugin capabilities. 1.1. What is ShardingSphere 3 Apache database protocols, SQL dialects, and database storage, it can quickly build standards on top of multi‐modal heterogeneous databases, while providing standardized connec‐ tion mode for applications through

with sharding, elastic scaling, encryption features & more. The project is committed to providing a multi‐source heterogeneous, enhanced database platform and further building an ecosystem around the upper needs. • Open Ecosystem It can provide users with flexibility thanks to custom systems based on multi‐level (kernel, feature, and ecosystem) plugin capabilities. 1.2 Design Philosophy ShardingSphere database protocols, SQL dialects, and database storage, it can quickly build standards on top of multi‐modal heterogeneous databases, while providing standardized connec‐ tion mode for applications through

with sharding, elastic scaling, encryption features & more. The project is committed to providing a multi‐source heterogeneous, enhanced database platform and further building an ecosystem around the upper needs. • Open Ecosystem It can provide users with flexibility thanks to custom systems based on multi‐level (kernel, feature, and ecosystem) plugin capabilities. 1.3. Advantages 3 2 Design Philosophy database protocols, SQL dialects, and database storage, it can quickly build standards on top of multi‐modal heterogeneous databases, while providing standardized connec‐ tion mode for applications through

with sharding, elastic scaling, encryption features & more. The project is committed to providing a multi‐source heterogeneous, enhanced database platform and further building an ecosystem around the upper needs. • Open Ecosystem It can provide users with flexibility thanks to custom systems based on multi‐level (kernel, feature, and ecosystem) plugin capabilities. 1.3. Advantages 3 2 Design Philosophy database protocols, SQL dialects, and database storage, it can quickly build standards on top of multi‐modal heterogeneous databases, while providing standardized connec‐ tion mode for applications through

It refers to a group of sharding tables with the same sharding rules. When using binding tables in multi‐ table correlating query, you must use the sharding key for correlation, otherwise Cartesian product so they are binding tables with each other. Cartesian product correlation will not appear in the multi‐tables correlating query, so the query efficiency will increase greatly. Take this one for example correctly. 4.6.5 Use Norms Supported • MySQL MGR single‐primary mode. Unsupported • MySQL MGR multi‐primary mode. 4.7 Scaling 4.7.1 Background There is a problem which how to migrate data from stand‐alone

It refers to a group of sharding tables with the same sharding rules. When using binding tables in multi‐ table correlating query, you must use the sharding key for correlation, otherwise Cartesian product so they are binding tables with each other. Cartesian product correlation will not appear in the multi‐tables correlating query, so the query efficiency will increase greatly. Take this one for example correctly. 4.6.5 Use Norms Supported • MySQL MGR single‐primary mode. Unsupported • MySQL MGR multi‐primary mode. 4.7 Scaling 4.7.1 Background There is a problem which how to migrate data from stand‐alone

_parameter.getTitle() + '%'" /> SELECT * FROM BLOG WHERE title LIKE #{pattern} Multi-db vendor support 一个配置了“_databaseId”变量的 databaseIdProvider 对于动态代码来说是可用的，这样就可以根据不同的数据库厂商构建特定的 语句。比如下面的例子：