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    Sysbench Benchmark Results
    Sysbench Benchmark Results
    Updated on 28 Apr 2026
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    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:

    Parameter Value
    Benchmark tool Sysbench (OLTP Read/Write)
    Number of tables 64
    Rows per table 1000000
    Workload type Read/Write
    Thread count Configured per instance size
    PostgreSQL version PostgreSQL 17

    Result:

    Flavor (vCPU/RAM) Thread count Sysbench Read Sysbench Write QPS TPS
    2C4G 64 2595600 741590 6177.66 308.88
    2C8G 64 2481276 708929 5905.53 295.27
    4C8G 64 3189018 911134 7589.71 379.48
    8C16G 64 4829286 1379738 11496.20 574.79
    8C32G 64 5679842 1622732 13519.46 675.94
    16C32G 64 6448036 1842199 15350.46 767.49
    16C64G 64 6926948 1979031 16489.02 824.41

    2.2. MySQL

    Test environment:

    Parameter Value
    Benchmark tool Sysbench (OLTP Read/Write)
    Number of tables 64
    Rows per table 1000000
    Workload type Read/Write
    Thread count Configured per instance size
    MySQL version MySQL 8.0.42

    Result:

    Flavor (vCPU/RAM) Thread count Sysbench Read Sysbench Write QPS TPS
    4C8G 16 6814500 1947000 16224.39 811.22
    8C16G 32 9748144 2785184 23209.29 1160.46
    8C32G 32 9423834 2692524 22430.67 1121.53
    16C32G 64 9786238 2796068 23289.48 1164.47

    2.3. MariaDB

    Test environment:

    Parameter Value
    Benchmark tool Sysbench (OLTP Read/Write)
    Number of tables 64
    Rows per table 1000000
    Workload type Read/Write
    Thread count Configured per instance size
    MySQL version MariaDB 10.6

    Result:

    Flavor (vCPU/RAM) Thread count Sysbench Read Sysbench Write QPS TPS
    4C8G 16 10573514 2111341 25174.34 1258.72
    8C16G 32 8923236 2094628 21245.25 1062.26
    8C32G 32 8491182 2086388 20216.52 1010.83
    16C32G 64 10267208 2568032 24444.58 1222.23
    16C64G 64 10789884 2719241 25688.30 1284.42

    2.4. MongoDB

    Test environment:

    Parameter Value
    Benchmark tool Sysbench (OLTP Read/Write)
    Number of documents 1.000.000
    Number of operations 1.000.000
    Workload type Read/Write
    Thread count (YCSB threads) Cấu hình tương ứng với từng flavor
    MongoDB version MongoDB 6.0.6

    Result:

    Flavor (vCPU/RAM) Thread count Sysbench Read Sysbench Write QPS TPS
    2C4G 8 500195 499805 3372.36 3372.36
    2C8G 8 500022 499978 4004.93 4004.93
    4C8G 16 499772 500228 5023.81 5023.81
    8C16G 32 500293 499707 6417.54 6417.54
    8C32G 32 500372 499628 5921.64 5921.64
    16C32G 64 499865 500135 8532.79 8532.79
    16C64G 64 499989 500011 12972.02 12972.02

    2.5. Redis

    Test environment:

    Parameter Value
    Benchmark tool Sysbench (OLTP Read/Write)
    Number of Key 1.000.000
    Workload type Read/Write
    Redis version Redis 7.2.1

    Result:

    Flavor (vCPU/RAM) Sysbench Read Sysbench Write Total QPS P99 latency AVG latency
    2C4G 68600 29405 98005.25 28.93 3.10
    2C8G 68346 29296 97641.61 30.85 3.92
    4C8G 67948 29126 97074.26 35.33 6.77
    8C16G 68655 29428 98083.03 28.03 3.41
    8C32G 67811 29067 96878.29 35.84 5.77
    16C32G 67964 29132 97096.07 33.54 4.89
    16C64G 68329 29289 97617.73 31.74 4.42

    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.

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