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drizzle-benchmarks
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# Drizzle Benchmarks Drizzle has always been fast, we just wanted you to have a meaningful [benchmarks experience](orm.drizzle.team#benchmarks) 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](./data/requests.json) 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: ```ts ... } const desiredPostgresPort = 5432; // change here main(); ``` 2. Update `DATABASE_URL` with allocated database port in .env file: ```env DATABASE_URL="postgres://postgres:postgres@localhost:5432/postgres" ``` 3. Seed your database with test data using `pnpm start:seed` command, you can change the size of the database in `./src/seed.ts` file: ```ts ... } main("micro"); // nano | micro ``` 4. Make sure you have Node version 18 installed or above, we've used Node v24. You can use [`nvm use 24`](https://github.com/nvm-sh/nvm) command 5. Start Drizzle/Prisma server: ```bash ## 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](https://k6.io/) 3. Run benchmarks 🚀 Use the built-in benchmark runner: ```bash 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 ``` 4. Prepare final combined results After benchmarks finish, merge all outputs into a single JSON file: ```bash tsx bench/prepare --folder results ```