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Description

GaussDB (for MySQL) represents a cutting-edge, enterprise-level distributed database service that is compatible with MySQL. It features a distinct architecture that separates compute and storage, utilizing data functions virtualization (DFV) storage which can automatically scale to accommodate up to 128 TB per database instance. The risk of data loss is essentially eliminated, and it is capable of handling millions of QPS throughputs while supporting cross-AZ deployments. This service effectively merges the high performance and dependability of commercial databases with the adaptability of open-source solutions. By decoupling compute and storage and connecting them via RDMA, along with implementing a "log as database" approach, users can achieve performance levels that are seven times greater than those of traditional open-source databases. Additionally, to enhance read capacity and performance, you can easily integrate up to 15 read replicas for a primary node within just minutes. GaussDB (for MySQL) ensures full compatibility with MySQL, allowing for a smooth migration of existing MySQL databases without the need for extensive application reconstruction or sharding, making it an ideal choice for businesses looking to upgrade their database systems. Overall, this innovative service provides an efficient solution for modern database management needs.

Description

PawSQL embodies the leading practices of query optimization within the database sector, offering sophisticated SQL rewrite enhancements and advanced index suggestions aimed at addressing sluggish queries. Leveraging the expertise of its professional optimization engine, which boasts a user base of over 10,000 database professionals globally, PawSQL delivers an extensive array of SQL optimization advice along with smart index recommendations. Additionally, it features a well-rounded audit rule framework designed for various database systems, including MySQL, PostgreSQL, openGauss, and Oracle, ensuring that enterprises enjoy a uniform auditing experience across their diverse database landscapes. The rule-oriented SQL evaluation focuses on identifying potential correctness flaws and opportunities for performance enhancement. By providing rich rewrite optimization, it suggests semantically equivalent yet more efficient SQL queries, while the cost-based validation confirms that the proposed solutions from SQL rewrites and index recommendations yield superior performance outcomes. Furthermore, PawSQL’s intelligent index recommendation feature enables users to optimize their query performance effectively.