From README to 30k Stars: How RustFS Became a Production-Ready MinIO Alternative

RustFS is an Apache-2.0 licensed, Rust-based distributed object storage system fully compatible with the S3 API. When first open-sourced in mid-2023, the repository contained only a README and a claim to replace MinIO, drawing skepticism. Over a year later, MinIO has archived its open-source community edition while RustFS has released a production-ready GA version.

Adoption and Production Readiness

RustFS reports over 2.7 million global installations, with more than 70% originating from the US and Europe. Several organizations already run it in production as paying customers, including TwinLabs (France), HyperApp (Uzbekistan), and multiple large Chinese enterprises. The core team consists of seven engineers who have collectively submitted thousands of commits, shipped over 100 releases, resolved more than 1,000 issues, and attracted 160+ contributors worldwide.

Seamless MinIO Migration

A headline feature of the GA release is direct MinIO data-disk compatibility. By setting the RUSTFS_VOLUMES parameter in /etc/default/rustfs to the existing MinIO data directory, RustFS can read the on-disk format without data copying. The article demonstrates the workflow on a test MinIO bucket containing 141 objects:

Install RustFS with

curl -O https://rustfs.com/install_rustfs.sh && bash install_rustfs.sh

Edit /etc/default/rustfs (example shown with access/secret keys, volumes pointing to "/data", API on :9000, console on :9001)

Start RustFS and access the console to see the original MinIO data immediately.

Free S3 Tables with Built-in Iceberg REST Catalog

RustFS embeds an Apache Iceberg REST Catalog directly into the storage kernel, exposing both standard S3 and Iceberg catalog endpoints from a single process and port. This enables Spark, DuckDB, and PyIceberg to create and query tables natively. MinIO offers the same capability only in its commercial edition at roughly 80,000 CNY per year. The article outlines the three-step setup:

Create a bucket.

Enable the bucket as a table bucket.

Write a Spark job to insert data.

AI Workload Relevance

The author notes RustFS repeatedly appears on GitHub Trending alongside AI projects. Two concrete drivers are identified: (1) RAG-style applications need a place to store documents, images, order records, etc., with controlled access for model consumption; (2) multimodal and embodied AI training pipelines generate massive datasets — images, audio, video, robot sensor logs — that require durable, high-throughput object storage for repeated reads during training.

Community-Driven Development

The release is framed as a "progress report" to the open-source community. The project's growth from a questioned README to a 30k-star GA version is attributed to incremental community contributions — bug reports, documentation fixes, code patches — illustrating the "take from community, give back to community" loop.

GitHub: github.com/rustfs/rustfs