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My personal tool for benchmarking database engines + some results in the README.

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DB-benchmark

This is my personal tool for benchmarking various database engines. It assesses the average time those engines take to complete the simplest tasks: creating one record, reading one record, updating one record and deleting one record.

My results

These are the results that I got for 10k executions on my hardware:

MongoDB MySQL NanoDB PostgreSQL
Create 0.17ms 10.62ms 1.58ms 2.77ms
Read 0.21ms 0.08ms 1.53ms 0.05ms
Update 0.21ms 10.60ms 1.57ms 2.82ms
Delete 0.20ms 11.15ms 1.54ms 2.86ms

System specifications:

Variable Specification
CPU i5-10300H
RAM 15.5GB
HDD WD10SPZX-24Z
Kernel 5.13.19-gentoo
FS ext4

How to use

  • Run pip install -r requirements.txt --user to install the required libraries;
  • Start the database engines;
  • Install additional engine-specific libraries and complete additional steps described in the table below;
  • Copy the .env.template file into .env and edit the defined variables to match your configuration;
  • Run ./app.py to start the benchmarking process.
Database engine Required libraries Additional steps
MongoDB pymongo --
MySQL mysql-connector-python Create a database and user for the app to utilise
NanoDB -- --
PostgreSQL psycopg2 Create a database and user for the app to utilise

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My personal tool for benchmarking database engines + some results in the README.

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