Drizzle Benchmarks

Drizzle has always been fast, we just wanted you to have a meaningful benchmarks experience

We ran our benchmarks on 2 separate machines, so that observer does not influence results. For database we're using PostgreSQL instance with 42MB of E-commerce data(~370k records).
K6 benchmarking instance lives on MacBook Air and makes 1M prepared requests through 1GB ethernet to Lenovo M720q with Intel Core i3-9100T and 32GB of RAM.

To run your own tests - follow instructions below!

Prepare test machine

1. Spin up a docker container with PostgreSQL using pnpm start:docker command. You can configure a desired database port in ./src/docker.ts file:

...
}

const desiredPostgresPort = 5432; // change here
main();

1. Update DATABASE_URL with allocated database port in .env file:

DATABASE_URL="postgres://postgres:postgres@localhost:5432/postgres"

1. Seed your database with test data using pnpm start:seed command, you can change the size of the database in ./src/seed.ts file:

...
}

main("micro"); // nano | micro

1. Make sure you have Node version 18 installed or above, we've used Node v24. You can use nvm use 24 command
2. Start Drizzle/Prisma server:

## Drizzle
pnpm start:drizzle

## Prisma
pnpm prepare:prisma
pnpm start:prisma

Prepare testing machine

1. Generate a list of http requests with pnpm start:generate. It will output a list of http requests to be run on the tested server | ./data/requests.json
2. Install k6 load tester
3. Run benchmarks 🚀
   Use the built-in benchmark runner:

tsx bench/index --host http://192.168.31.144:3000 --name my-bench --folder results

http://192.168.31.144:3000 // drizzle
http://192.168.31.144:3001 // prisma

1. Prepare final combined results
   After benchmarks finish, merge all outputs into a single JSON file:

tsx bench/prepare --folder results