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Benchmark with Sysbench

This section presents database performance benchmark results performed using the Sysbench tool, aiming to provide a reference for the processing capabilities of database engines across different compute configurations (flavors). The results are provided for reference purposes only and do not represent guaranteed performance.

1. Benchmark Sysbench Overview

Purpose:

  • Evaluate OLTP (Read/Write) performance of supported database engines.
  • Observe performance scaling behavior when increasing CPU and memory resources.
  • Provide reference data to assist customers in selecting appropriate instance sizes.

Benchmarked database engines: The database engines are included in this benchmark: PostgreSQL, MySQL, and MariaDB. Metrics:

  • Sysbench Read : Total number of read queries executed during the test.
  • Sysbench Write : Total number of write queries executed during the test.
  • QPS (Queries Per Second) : Average number of queries processed per second.
  • TPS (Transactions Per Second) : Average number of completed transactions per second.

Higher QPS and TPS values indicate higher throughput under the tested workload.

2. Benchmark Results by Database Engine

2.1. PostgreSQL

Test environment:

ParameterValue
Benchmark toolSysbench (OLTP Read/Write)
Number of tables64
Rows per table1000000
Workload typeRead/Write
Thread countConfigured per instance size
PostgreSQL versionPostgreSQL 17
Result:
Flavor (vCPU/RAM)Thread count
------
2C4G64
2C8G64
4C8G64
8C16G64
8C32G64
16C32G64
16C64G64

2.2. MySQL

Test environment:

ParameterValue
Benchmark toolSysbench (OLTP Read/Write)
Number of tables64
Rows per table1000000
Workload typeRead/Write
Thread countConfigured per instance size
MySQL versionMySQL 8.0.42
Result:
Flavor (vCPU/RAM)Thread count
------
4C8G16
8C16G32
8C32G32
16C32G64

2.3. MariaDB

Test environment:

ParameterValue
Benchmark toolSysbench (OLTP Read/Write)
Number of tables64
Rows per table1000000
Workload typeRead/Write
Thread countConfigured per instance size
MySQL versionMariaDB 10.6
Result:
Flavor (vCPU/RAM)Thread count
------
4C8G16
8C16G32
8C32G32
16C32G64
16C64G64

3. Analysis & Recommendations

  • Increasing CPU and memory generally improves throughput.
  • Each database engine exhibits different scaling characteristics.
  • Performance gains may diminish at higher configurations depending on workload and system limits.

Important:

  • Benchmark results are workload-specific and provided for reference only.
  • Actual performance may vary depending on:
    • Application workload characteristics.
    • Database schema and indexing.
    • Read/write ratio.
    • Storage and network configuration.

Customers are strongly encouraged to test with their own workloads before deploying to production. Recommendations: Use these benchmark results as guidance when selecting database engines and instance sizes. For optimal performance, validate configuration choices through application-specific performance testing.