Awesome

Watermill Benchmark

This is a set of tools for benchmarking watermill.

Warning: This tool is meant to provide a rough estimate on how fast each Pub/Sub can process messages. It uses very simplified infrastructure to set things up and default configurations.

Keep in mind that final performance depends on multiple factors.

It's not meant to be a definitive answer on which Pub/Sub is the fastest. It should give you an idea of the ballpark performance you can expect.

How it works

All tests are run on a single 16 CPU GCloud compute instance (n1-highcpu-16).
Docker Compose is used to run Pub/Sub infrastructure and benchmark code (except for Google Cloud Pub/Sub).
The tool will first produce a big number of messages on a generated topic.
Then it will subscribe to the topic and consume all of the messages.
Multiple message sizes can be chosen (by default: 16, 64 and 256 bytes).

Results (as of 18 November 2024)

Kafka (one node)

Message size (bytes)	Publish (messages / s)	Subscribe (messages / s)
16	41,492	101,669
64	40,189	106,264
256	40,044	107,278

NATS Jetstream (16 Subscribers)

Message size (bytes)	Publish (messages / s)	Subscribe (messages / s)	Subscribe (messages / s - async ack)
16	50,668	34,713	59,728
64	49,204	34,561	59,743
256	48,242	34,097	59,385

NATS Jetstream (48 Subscribers)

Message size (bytes)	Publish (messages / s)	Subscribe (messages /s )	Subscribe (messages / s - async ack)
16	50,680	46,377	86,348
64	49,341	46,307	86,078
256	48,744	46,035	86,499

Redis

Message size (bytes)	Publish (messages / s)	Subscribe (messages / s)
16	59,158	12,134
64	58,988	12,392
256	58,038	12,133

SQL (MySQL)

Message size (bytes)	Publish (messages / s)	Subscribe (messages / s - batch size = 1)	Subscribe (messages / s - batch size = 100)
16	6,371	283	2,794
64	9,887	281	2,637
256	9,596	271	2,766

SQL (PostgreSQL)

Message size (bytes)	Publish (messages / s)	Subscribe (messages / s - batch size = 1)	Subscribe (messages / s - batch size = 100)
16	2,552	122	9,460
64	2,831	118	9,045
256	2,744	104	7,843

SQL (PostgreSQL Queue)

Subscribe Batch Size	Message size (bytes)	Publish (messages / s)	Subscribe (messages / s - batch size = 1)	Subscribe (messages / s - batch size = 100)
100	16	2,825	146	10,466
100	64	2,842	147	9,626
100	256	2,845	138	8,276

Message size (bytes)	Publish (messages / s)	Subscribe (messages / s)
16	2,825	0,146
64	2,842	0,147
256	2,845	0,138

Google Cloud Pub/Sub (16 subscribers)

Message size (bytes)	Publish (messages / s)	Subscribe (messages / s)
16	3,027	28,589
64	3,020	31,057
256	2,918	32,722

AMQP (RabbitMQ, 16 subscribers)

Message size (bytes)	Publish (messages / s)	Subscribe (messages / s)
16	2,770	14,604
64	2,752	12,128
256	2,750	8,550

GoChannel

Message size (bytes)	Publish (messages / s)	Subscribe (messages / s)
16	315,776	138,743
64	325,341	163,034
256	341,223	145,718

VM Setup

The project includes Terraform definition for setting up an instance on Google Cloud Platform.

It will spin up a fresh Ubuntu 19.04 instance, install docker with dependencies and clone this repository.

Set environment variables:

# project name on GCP
TF_VAR_project=
# public part of the key that you will use to access SSH
TF_VAR_pub_key_path=

Create the VM:

cd setup
terraform apply

The command will output the public IP address of the server. Use ssh with user benchmark to access it.

After running all benchmarks, destroy the VM:

terraform destroy

Configuration

Google Pub/Sub

Set environment variables in compose/.env:

# path to json file within the project with GCP credentials
GOOGLE_APPLICATION_CREDENTIALS=compose/key.json
# project name on GCP
GOOGLE_CLOUD_PROJECT=

Running

Run benchmarks with:

./run.sh <pubsub>