SeaweedFS and RustFS share an important characteristic that can make them look like direct alternatives: both are open-source projects released under Apache 2.0, and both can be deployed as a single binary. But they are designed for different jobs. SeaweedFS combines S3 object storage with a distributed file system capable of handling billions of files, while RustFS focuses on S3-compatible object storage and aims to provide a simple alternative for teams already familiar with MinIO.

The key points about SeaweedFS and RustFS in 30 seconds

SeaweedFS combines S3, a file system, FUSE and lakehouse capabilities over the same underlying data.
RustFS focuses on S3, with MinIO-oriented compatibility and a web console.
SeaweedFS uses a 16-byte in-memory index per object and stores 40 bytes of metadata per file.
RustFS offers a simpler operational model for teams that only need S3 object storage.
The right choice depends mainly on whether the project needs a file-system interface or only an object-storage API.

The difference may sound technical, but it has direct consequences for development teams. Choosing SeaweedFS when the only requirement is S3 can add capabilities that will never be used. Choosing RustFS for an application that needs to mount its data as a file system, on the other hand, means working outside capabilities the project currently provides.

The decision should therefore start with the interface the application needs and the type of data it will store.

SeaweedFS is designed for huge numbers of files

SeaweedFS presents itself as a distributed file system that also provides S3 object storage. Its architecture allows the same underlying data to be accessed through several interfaces, including S3, a POSIX file system, FUSE, WebDAV, SFTP, HDFS and an Apache Iceberg REST catalog.

Its design becomes particularly interesting as the number of files grows. The master server does not keep individual information about every file. Instead, it tracks the volumes where the data is stored.

Volume servers store objects in append-only volume files and maintain a 16-byte in-memory index per object. On disk, the system uses 40 bytes of metadata per file.

The result is that the master does not need to maintain a structure equivalent to one individual record for every file. According to the project’s documentation, a cluster containing billions of files can continue operating with a relatively small number of volumes.

This also means that the master does not have to participate in every read. Clients can cache the relationship between volumes and servers and communicate directly with volume servers.

For content-addressable storage, photo and video libraries, large content repositories or AI workloads containing huge numbers of small shards, this architecture can make a significant difference.

SeaweedFS also includes erasure coding for warm data. The system can keep hot data replicated for performance and apply erasure coding in the background.

RustFS reduces storage to its S3 interface

RustFS takes a different approach. Written in Rust, it presents itself as S3-compatible object storage with a focus on the MinIO ecosystem and a web console.

It can be deployed as a single binary or container. The project’s documentation shows a simple Docker-based deployment exposing the S3 API on port 9000 and the console on port 9001.

That simplicity is one of its main arguments. A team that only needs an S3 endpoint does not have to deploy a file-system layer or manage an architecture designed for additional access methods.

The RustFS documentation lists features including versioning, Object Lock (WORM), lifecycle management, bucket replication, site replication, IAM (identity and access management), policies, OIDC/SSO, server-side encryption and distributed mode.

S3 Tables through Iceberg REST is also listed, but as a preview feature. That distinction matters for teams looking to build a lakehouse on top of their storage and requiring mature production capabilities.

RustFS also currently lacks a FUSE or POSIX layer. For an application that only interacts with objects through S3, that may not matter at all. For software that needs to mount storage as a directory, it changes the decision completely.

MinIO compatibility also matters

Both projects use Apache 2.0, so licensing is not a major differentiator.

The more important question is how closely each project is aligned with the requirements of the application. SeaweedFS implements S3 as one interface on top of its distributed file system. RustFS puts S3 at the center of its design.

For an organization whose applications already work with the MinIO ecosystem, RustFS can be a more direct option. Its goal is to provide S3-compatible storage with a relatively small operational surface.

That does not mean SeaweedFS is incompatible with S3 clients. The difference is that it was not designed exclusively around that interface.

SeaweedFS documentation reflects this broader approach: the same storage can be accessed by applications using S3 and by tools requiring a file-system interface or a lakehouse catalog.

The decision changes once the requirement goes beyond S3.

What happens with performance and metadata?

SeaweedFS publishes a performance reference in its documentation showing one million 1 KB files at concurrency 16 on a MacBook with an SSD. The project itself describes this as an unscientific single-machine measurement, so it should be treated as a scale reference rather than a direct benchmark between SeaweedFS and RustFS.

RustFS does not publish an equivalent per-object index-size figure in the source material analyzed. It would therefore be incorrect to claim that both systems behave identically when handling billions of files.

Memory usage also needs to be considered in terms of architecture. SeaweedFS explicitly documents a design intended to prevent the master from maintaining an individual entry for every file. RustFS focuses instead on providing S3 storage with a simpler operational model.

These are not two implementations of exactly the same product. They are two different approaches to storage that overlap in some scenarios.

The decision comes down to one practical question

A simple rule can help separate the use cases.

If the requirements mention file system, FUSE or lakehouse, SeaweedFS should be among the first options to evaluate. Its ability to provide several interfaces over the same data is a central part of its design.

If the requirement is simply S3, particularly when the team values operational simplicity and MinIO compatibility, RustFS is more closely aligned with that scenario.

It is also possible to use both in the same architecture. SeaweedFS can handle file-system and lakehouse workloads, while RustFS can provide an S3 endpoint for applications whose only contract with storage is the S3 API.

The mistake would be trying to make one replace the other in a role it was not designed for.

SeaweedFS brings file-system capabilities that an S3-only team may never use. RustFS, meanwhile, does not currently provide the POSIX/FUSE layer required by an application that needs to treat storage as a local directory.

The choice is therefore less about which project has more features and more about which features actually solve the problem.

Frequently asked questions

Is SeaweedFS a direct replacement for MinIO?

Not exactly. SeaweedFS provides S3 as one of several interfaces on top of its distributed file system, while RustFS is designed around S3 and targets closer compatibility with the MinIO ecosystem.

Does RustFS support FUSE?

Not according to the feature table analyzed in its documentation. If an application needs to mount storage through FUSE or use a POSIX interface, SeaweedFS provides that capability.

Which one is designed for billions of files?

SeaweedFS is specifically designed for that scenario. Its master tracks volumes rather than individual files, while the project uses a 16-byte in-memory index per object.