How to parse Sharding JDBC
How to analyze Sharding JDBC, I believe that many inexperienced people are at a loss about it. Therefore, this paper summarizes the causes and solutions of the problem. Through this article, I hope you can solve this problem.
Sharding JDBC introduction
Sharding-JDBC is an open source distributed database middleware developed by Dangdang. Sharding-JDBC has been included in Sharding-Sphere since 3.0. after that, the project entered the Apache incubator, followed by the Apache version.
ShardingSphere is an ecological circle of open source distributed database middleware solutions made up of three independent products, Sharding-JDBC,Sharding-Proxy and Sharding-Sidecar (planned). They all provide standardized data fragmentation, distributed transactions and database governance functions.
At present, we only need to focus on Sharding-JDBC, which is positioned as a lightweight Java framework, providing additional services in the JDBC layer of Java, providing services in the form of jar packages, without additional deployment and dependency, can be understood as an enhanced version of the JDBC driver, fully compatible with JDBC and various ORM frameworks.
The core functions of Sharding-JDBC are data slicing and read-write separation. Through Sharding-JDBC, applications can use JDBC to access each database transparently, regardless of the number of data sources and how the data is distributed.
Performance comparison with JDBC
1. Performance loss test: in the case of sufficient server resources and the same number of concurrency, comparing the performance loss of JDBC and Sharding-JDBC, the loss of Sharding-JDBC relative to JDBC is no more than 7%.
Benchmark performance comparison:
two。 Performance comparison test: server resources are used to the limit, and the throughput of JDBC and Sharding-JDBC is the same in the same scenario.
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