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TDSQL-C for MySQL

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Performance Overview

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Last updated: 2025-12-25 09:45:59
TDSQL-C for MySQL is a Tencent Cloud self-developed new-generation cloud native relational database, which has the strengths of traditional databases, cloud computing, and new hardware technologies, and is 100% compatible with MySQL, providing users with flexible and secure high-performance database services that are highly available and reliable. 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 total solutions for database Ops, including data backup, recovery, monitoring, rapid scale-out, and data transmission. It simplifies your IT Ops work and allows you to focus more on business development.
After continuous tests and optimization by professional teams, TDSQL-C for MySQL provides various MySQL Enterprise Edition features. Its engine kernel has been further optimized to deliver flexible and efficient transaction processing capabilities, and the advanced and complete capabilities of compliance and security protection. With ultra-large instance capacity, TDSQL-C for MySQL features superior performance.
This section mainly introduces the performance test of TDSQL-C for MySQL, including the test environment, tool, method, and result. For the two data set characteristics, full cache and large data set, the performance test is performed in read-only, mixed read-write, and write-only scenarios to show the overall performance of TDSQL-C for MySQL.
Note:
The general clusters mentioned in this section refer to those created on the purchase page. For details about the creation method, see Creating a Cluster.
The compilation-optimized high-performance version mentioned in this section refers to the version with an optimized kernel. You need to apply to use this version through the ticket system. For details about this version, see Compilation-Optimized High-Performance Version.

Overview of Performance Test Sections

Category
Documentation Link
Description
Test element
Introduces the performance test environments and provides information about the test objects.
Introduces the performance test tools and how to install the tool on a Cloud Virtual Machine (CVM) instance.
Introduces the performance test method, including the related commands and parameters.
Introduces the performance test metrics.
Test results (for general clusters)
Introduces the performance test results for general clusters in read-only, mixed read-write, and write-only scenarios where the data set characteristic is full cache.
Introduces the performance test results for general clusters in read-only, mixed read-write, and write-only scenarios where the data set characteristic is large data set.
Test results (compilation-optimized high-performance version)
Introduces the performance test results for the compilation-optimized high-performance version in read-only, mixed read-write, and write-only scenarios where the data set characteristic is full cache.
Introduces the performance test results for the compilation-optimized high-performance version in read-only, mixed read-write, and write-only scenarios where the data set characteristic is large data set.

Test Scenarios and Read Types

The test scenarios of full cache and large data set and the corresponding read types for the performance test are provided in the table below.
Note:
range select and point select in the table are defined as follows:
range select: Range test, which indicates the number of range select queries in a single transaction.
point select: Point test, which indicates the number of point select queries in a single transaction.
Data Set Characteristic
Test Scenario
Test Condition
Read Type
Full cache
Large data set
Read-only
Binlog enabled
range select
point select
Mixed read-write
Binlog enabled
range select
point select
Write-only
Binlog enabled
-

Test Results

Test results for general clusters are as follows:
Test results for the compilation-optimized high-performance version are as follows:

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