TencentDB for PostgreSQL
- Release Notes and Announcements
- Announcements
- Product Introduction
- Purchase Guide
- Getting Started
- Kernel Version Introduction
- Operation Guide
- Instance Management
- Upgrading Instance
- Read-Only Instance
- Account Management
- Database Management
- Database Optimization
- Parameter Management
- Log Management and Analysis
- Backup and Restoration
- Data Migration
- DTS-Based Logical Migration
- Verification Failure Handling
- Physical migration based on DTS
- Database Audit
- Extension Management
- Supported Extensions
- Network Management
- Data Security
- Tenant and Resource Isolation
- Monitoring and Alarms
- MSSQL Compatible Version
- Practical Tutorial
- Performance White Paper
- API Documentation
- Making API Requests
- Instance APIs
- Read-only Replica APIs
- Backup and Recovery APIs
- Parameter Management APIs
- Security Group APIs
- Performance Optimization APIs
- Specification APIs
- PostgreSQL for Serverless APIs
- Network APIs
- Service Agreement
Test Results
Last updated: 2024-08-09 15:24:42
This document will verify the performance data of TencentDB for PostgreSQL in write-only, read-only and read-write scenarios of Sysbench.
Scenario 1: Full Cache
In the full cache scenario, all data can be stored in the cache, so there is no need to read or write the disk to update the cache during the query process.
Write-only
Instance specifications | Concurrency | Single-table data size (table_size) | Total number of tables (tables) | QPS | TPS |
1-core 2 GB memory | 32 | 25000 | 64 | 21308.50 | 3551.41 |
4-core 16 GB memory | 32 | 25000 | 64 | 139100.86 | 23183.37 |
8-core 32 GB memory | 64 | 25000 | 64 | 219394.80 | 36565.50 |
48-core 480 GB memory | 512 | 25000 | 256 | 357198.25 | 59531.89 |
Read-only
Instance specifications | Concurrency | Single-table data size (table_size) | Total number of tables (tables) | QPS | TPS |
1-core 2 GB memory | 32 | 25000 | 64 | 26327.01 | 1645.44 |
4-core 16 GB memory | 32 | 25000 | 64 | 111475.78 | 6967.24 |
8-core 32 GB memory | 64 | 25000 | 64 | 179257.13 | 11203.57 |
48-core 480 GB memory | 512 | 25000 | 256 | 346572.52 | 21660.78 |
Read-write
Instance specifications | Concurrency | Single-table data size (table_size) | Total number of tables (tables) | QPS | TPS |
1-core 2 GB memory | 32 | 25000 | 64 | 17282.27 | 864.11 |
4-core 16 GB memory | 32 | 25000 | 64 | 80646.27 | 4032.31 |
8-core 32 GB memory | 64 | 25000 | 64 | 115549.05 | 5777.44 |
48-core 480 GB memory | 256 | 25000 | 256 | 173502.17 | 8675.04 |
Scenario 2: Big Dataset
In the big dataset scenario, all data cannot be stored in the cache (the data size is more than twice the memory size), so the disk needs to be read and written to update the cache during the query process.
Write-only
Instance specifications | Concurrency | Single-table data size (table_size) | Total number of tables (tables) | QPS | TPS |
1-core 2 GB memory | 32 | 10000000 | 64 | 16973.36 | 2828.89 |
4-core 16 GB memory | 32 | 10000000 | 64 | 64245.25 | 10707.54 |
8-core 32 GB memory | 64 | 10000000 | 64 | 100686.77 | 16781.13 |
48-core 480 GB memory | 256 | 10000000 | 640 | 125237.97 | 20873.00 |
Read-only
Instance specifications | Concurrency | Single-table data size (table_size) | Total number of tables (tables) | QPS | TPS |
1-core 2 GB memory | 32 | 10000000 | 64 | 14407.49 | 900.47 |
4-core 16 GB memory | 32 | 10000000 | 64 | 58952.38 | 3684.52 |
8-core 32 GB memory | 64 | 10000000 | 64 | 87727.56 | 5482.97 |
48-core 480 GB memory | 512 | 10000000 | 640 | 137603.21 | 8600.20 |
Read-write
Instance specifications | Concurrency | Single-table data size (table_size) | Total number of tables (tables) | QPS | TPS |
1-core 2 GB memory | 32 | 10000000 | 64 | 13655.23 | 682.76 |
4-core 16 GB memory | 32 | 10000000 | 64 | 58426.87 | 2921.34 |
8-core 32 GB memory | 64 | 10000000 | 64 | 80741.40 | 4037.07 |
48-core 480 GB memory | 256 | 10000000 | 640 | 114922.98 | 5746.15 |
Was this page helpful?
You can also Contact Sales or Submit a Ticket for help.
Yes
No