Performance Overview
Last updated: 2025-12-10 14:30:52
TDSQL-C for MySQL (TDSQL-C for MySQL) is a self-developed new-generation cloud-native relational database by Tencent Cloud. It integrates the advantages of traditional databases, cloud computing, and new hardware technologies, is 100% compatible with MySQL, and provides users with flexible elasticity, high performance, high availability, high reliability, and secure database services. It achieves high throughput of over one million QPS, PB-level massive distributed intelligent storage, and Serverless second-level scaling, helping enterprises accelerate their digital transformation.
TDSQL-C for MySQL provides a comprehensive solution for database Ops including backup, recovery, monitoring, rapid scaling, data transmission, and so on, simplifying your IT Ops work and allowing you to focus more on business development.
TDSQL-C for MySQL, after continuous testing and optimization by a professional team, provides various MySQL Enterprise Edition features. Its engine kernel has been extensively optimized to deliver flexible and efficient capabilities of processing transactions, advanced comprehensive compliance and security protection, and ultra-large instance capacity, enabling superior and robust performance.
This section primarily introduces the aspects of performance testing for TDSQL-C for MySQL, including test environment, testing tools, testing methods, test results, and so on. It targets two dataset characteristics—fully cached and large dataset—and conducts performance testing in read-only, mixed read/write, and write-only scenarios, thereby showcasing the overall performance of TDSQL-C for MySQL.
Note:
TDSQL-C for MySQL has been significantly upgraded. The new version architecture adopts end-to-end RDMA, optimizes multiple performance aspects based on the enterprise-grade TXSQL kernel, upgrades the architecture of the distributed storage layer, and provides new hardware support. The new architecture is now available in Guangzhou Zone 7 and is currently in public beta. You can submit a ticket to obtain public beta eligibility.
Performance Testing Section Overview
Category | Documentation | Description |
Testing Elements | Introducing the environment and information about the test object used in performance testing. | |
| Introducing the testing tools used in performance testing and how to install them on CVM instances. | |
| Introducing the testing methods for performance testing, including running commands and parameter explanations. | |
| Introducing the test metrics for performance testing. | |
Test Result | Introducing the performance test results under read-only, mixed read-write, and write-only scenarios with fully cached dataset characteristics. | |
| Introducing the results of performance tests under read-only, mixed read-write, and write-only scenarios with large dataset characteristics. | |
Test Scenarios and Read Types
This performance test targets the testing scenarios for fully cached and large datasets, and their corresponding read types are shown in the table below.
Note:
In the table, range select and point select are defined as follows:
range select: Range test, which indicates the number of queries for tests for range selection in a single transaction.
point select: Point test, which indicates the number of queries for tests for point selection in a single transaction.
Dataset Characteristics | Test Scenario | Test Conditions | Read Type |
Fully-Cached large dataset | Read-Only | enable binlog | range select |
| | | point select |
| Mixed Read/Write | enable binlog | range select |
| | | point select |
| Write-Only | enable binlog | - |
Test Results
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