This repository has been archived by the owner on Dec 19, 2023. It is now read-only.

Name		Name	Last commit message	Last commit date
parent directory ..
DB_Performance__Normalized_.svg		DB_Performance__Normalized_.svg
DB_Performance__Ops_Sec_.svg		DB_Performance__Ops_Sec_.svg
README.md		README.md
benchmarks.json		benchmarks.json
main.py		main.py
tests.py		tests.py

README.md

Database performance

This benchmark report was generated by main.py.

	Find Entry	Insert Dump	Remove Entry	Upsert Entry
MongoDB	1,373.88	14,199.87	572.77	2,516.66
MySQL	649.42	14,636.07	885.60	373.24
PostgreSQL	689.94	7,230.86	897.67	547.85
SQLite	487.21	44,137.56	469.26	372.24

Lets add some colors!

	Find Entry	Insert Dump	Remove Entry	Upsert Entry	Mean Result
MongoDB	1,373.88	14,199.87	572.77	2,516.66	👎
MySQL	649.42	14,636.07	885.60	373.24	👎
PostgreSQL	689.94	7,230.86	897.67	547.85	👎
SQLite	487.21	44,137.56	469.26	372.24	🍓🍓🍓

Or a ranking?

	Find Entry	Insert Dump	Remove Entry	Upsert Entry	Upsert Entry Ranking
MongoDB	1,373.88	14,199.87	572.77	2,516.66	🥇
MySQL	649.42	14,636.07	885.60	373.24	🥉
PostgreSQL	689.94	7,230.86	897.67	547.85	🥈
SQLite	487.21	44,137.56	469.26	372.24	# 4

Define a baseline and see the gains!

	Find Entry	Mean Gains
SQLite	487.21	1x
MySQL	649.42	1.33x
PostgreSQL	689.94	1.42x
MongoDB	1,373.88	2.82x

Render charts with Plotly!