INTRODUCTION

The purposes of this research are next:

1. Compare the performance of most commonly used frameworks, languages, and libraries;
2. Gain the experience in different non-related to previous primary focused stack, be hands-on with neighbor technologies;
3. Share results with the global community all over the world;

---

COMMON INFORMATION

• I disabled all application levels caches to get clear performance metrics of the server as it is;
• The database and application are running in the same network to avoid net lags and penalties;
• The fetching strategy is EAGER. First, to do a higher load and non-optimized queries to database. Second, not to spend time to setup entity graphs.
• The average time to boot up the service will not depend on the database structure due to the fact that I am not using any database migration tools such as Flyway or Liquibase;
• All database structures had been already prepared and filled with faked data;
• As a load testing tool I chose Gatling;
• The versions of all languages, frameworks, libraries, and databases are the latest LTS at the moment of testing.

---

DATABASE STRUCTURE

---

DATASET DESCRIPTION

The definition of database init script and docker-compose file.

To connect via pgadmin follow pgadmin enter "user@user.com" and "password". Create server and attach to host docker inspect $(docker ps -aqf "name=postgres") | grep IPAddress, port "5433", db "postgres" with "user" and "password" credentials.

UNIT	AMOUNT
Countries	1
Cities	6
Locations	120
Transfers	12000
Users	200000
Users_Transfers	500000

For a generation of the dataset, I've created the other module datagen. I will not dive deeper into data generation process. You could easily check out how it works in sources. After that, I got DB size, and DB dump, and created a separate docker image with the predefined dataset. This docker image is located in every tested module directory.

The DB metrics:

Postgres 14.2:

• Database size: 153 MB
• Database dump size: 130.8 MB
• Docker image with predefined data: 160.01 MB

Postgres 16.1:

• Database size: 139 MB
• Database dump size: 137.23 MB
• Docker image with predefined data: 147.55 MB

---

USE CASES

#	Scenario step	Assumed operation
1	As a user I would like to choose the country.	[GET] The list of available countries is presented.
2	As a user I would like to choose the city.	[GET] The list of available cities is presented.
3	As a user I would like to choose the origin.	[GET] The list of available origins is presented.
4	As a user I would like to choose the destination.	[GET] The list of available destinations is presented.
5	As a user I would like to choose the date of transfer.	[GET] [NO LOAD] The future dates for the current month are presented.
6	As a user I would like to see all available transfers from 'origin', to 'destination' for selected this date.	[GET] The list of available transfers by selected origin, destination, and date is presented.
7	As a user I would like to book a transfer.	[POST] The transfer is booked in the system.
8	As a user I would like to see all my transfers.	[GET] The list of all my transfers (COMPLETED, CANCELED, BOOKED) is presented.
9	As a user I would like to view any owned transfer.	[GET] One of the transfers (COMPLETED, CANCELED, BOOKED) is retrieved.
10	As a user I would like to edit any owned transfer in the future.	[PUT] Any (BOOKED) transfer description is updated.
11	As a user I would like to cancel any owned transfer in the future.	[PUT] Any (BOOKED) transfer is canceled (CANCELED).
12	As a user I would like to complete any owned transfer in the past.	[PUT] Any (BOOKED) transfer is completed (COMPLETED).
13	As a user I would like to see my profile.	[GET] User is retrieved with her/his transfers data.
14	As a user I would like to update my profile.	[PUT] User updates with her/his own data.
15	Repeat (1) - (9) 20 minutes for each user.

The application is a transportation service.

Let's assume that the average user has the biggest interest to book the transfer from 8:00 till 00:00. As a result, we will have 16 per day and 112 hours of load per week.

I've described all use cases endpoints via OpenAPI.

---

RESULTS

FRAMEWORK	APPLICATION TYPE	BUILD TYPE	BUILD TIME (s)	ARTIFACT SIZE (MB)	BOOT UP (s)	TOTAL REQUESTS	KO(%)	RPS	RESPONSE TIME (95th pct) (ms)	SATURATION POINT	RAM (MB)	CPU (%)	THREADS (MAX)	POSTGRES CPU (%)
SPRING	WEB	NATIVE BUILD PACK	751	144.79	1,585	453012	25	374.566	47831	584	310	12.5	64	99
		NATIVE BUILD TOOLS	210	116.20	0.310	480763	29	414.785	32175	1829	263	8	52	99
		TOMCAT	5	49.70	3.59	523756	24	381.127	50977	1611	658	11	33	99
		TOMCAT IN DOCKER	46	280	5.20	430673	33	448.682	29998	916	840	15	32	99
	REACTIVE + R2DBC	NATIVE BUILD PACK	1243	98.5	0.103	691487	17	615.750	17891	1904	685	30	14	70
		NATIVE BUILD TOOLS	187	71.7	0,107	1013549	10	934.147	12591	3038	634	32	23	70
		JAR	3.1	40.6	2.55	1168782	8	1091.30	10406	4391	1823	8	31	70
		JAR IN DOCKER	39	271	3.95	699180	17	631.599	18955	2250	883	29	31	70
QUARKUS	REACTIVE + R2DBC	FAST JAR	4	N/A	0.987	828711	13	755.434	13686	1971	1054	9	25	99
		UBER JAR	8	17.7	1.884	826311	13	753.933	14111	2149	989	5	23	99
		JIB WITH UBI	16	384	1.151	661502	18	593.275	20170	1305	1054	8	26	70
		JIB WITH DISTROLESS	14	249	1.088	473991	20	540.492	33060	1339	970	8	26	93
		DOCKER	39	416	0.948	609675	28	428.563	24206	1315	262	18	21	53
		NATIVE EXECUTABLE	180	49.3	0.223	768017	15	697.563	16426	1967	646	10	15	99
	+ UPX-MAX	NATIVE EXECUTABLE	741	15	N/A	N/A	N/A	N/A	N/A	N/A	N/A	N/A	N/A	N/A
		NATIVE MICRO BASE IMAGE	301	78.6	0.031	570959	22	507.971	25637	1282	690	20	8	57
		NATIVE MINIMAL BASE IMAGE	301	152	0.025	523534	25	448.231	35777	914	669	17	8	61
		NATIVE DISTROLESS BASE IMAGE	238	72.1	0.032	546371	23	473.458	30156	1747	622	23	8	45
MICRONAUT	REACTIVE + R2DBC	JAR	17	21.4	1.176	683907	17	616.132	19540	2487	4495	10	49	75
		DEFAULT DOCKER IMAGE	74	346	2.373	488076	27	425.895	41730	1189	586	59	23	26
		JIB	21	252	1.767	489590	27	416.672	37474	1023	586	26	60	31
		NATIVE EXECUTABLE	188	78	0.042	604610	20	534.580	25728	1717	762	38	35	65
		DEFAULT NATIVE DOCKER IMAGE	457	99.3	0.115	371624	44	338.455	46090	1072	419.2	50	14	25
		AOT OPTIMIZED DOCKER IMAGE	5808	99.4	0.088	339333	49	308.204	53506	1095	381	60	15	12

• SPRING WEB AND SPRING WEB AS NATIVE
• SPRING REACTIVE AND SPRING REACTIVE AS NATIVE
• QUARKUS REACTIVE AND QUARKUS REACTIVE AS NATIVE
• MICRONAUT REACTIVE AND MICRONAUT REACTIVE AS NATIVE

---

SUPPORT THE PROJECT

• TON: vadzimkavalkou