diff --git a/mkdocs/docs/configuration.md b/mkdocs/docs/configuration.md
index 44b5e395a9..a6dfa24f38 100644
--- a/mkdocs/docs/configuration.md
+++ b/mkdocs/docs/configuration.md
@@ -242,6 +242,21 @@ Tencent Cloud Object Storage (COS) is S3-compatible and can be used with PyIcebe
 
 <!-- markdown-link-check-enable -->
 
+### SeaweedFS
+
+<!-- markdown-link-check-disable -->
+
+[SeaweedFS](https://github.com/seaweedfs/seaweedfs) is S3-compatible and can be used with PyIceberg using the existing S3FileIO / PyArrowFileIO implementation.
+
+| Key                  | Example                 | Description                       |
+| -------------------- | ----------------------- | --------------------------------- |
+| s3.endpoint          | <http://localhost:8333> | SeaweedFS S3 gateway endpoint     |
+| s3.access-key-id     | admin                   | Configured S3 access key          |
+| s3.secret-access-key | password                | Configured S3 secret key          |
+| s3.path-style-access | true                    | SeaweedFS serves path-style URLs  |
+
+<!-- markdown-link-check-enable -->
+
 ### Hugging Face
 
 <!-- markdown-link-check-disable -->
@@ -653,6 +668,23 @@ catalog:
     Use the `entra` auth type for Entra ID (Azure AD) authentication via [DefaultAzureCredential](https://learn.microsoft.com/en-us/azure/developer/python/sdk/authentication/credential-chains?tabs=dac#defaultazurecredential-overview), which supports environment variables, managed identity, Azure CLI, and more. Install with `pip install pyiceberg[entra-auth]`.
 <!-- prettier-ignore-end -->
 
+##### SeaweedFS Table Buckets
+
+[SeaweedFS](https://github.com/seaweedfs/seaweedfs) table buckets serve an Iceberg REST catalog for table metadata and store the table data as Parquet files behind the same S3 gateway:
+
+```yaml
+catalog:
+  seaweedfs_catalog:
+    type: rest
+    uri: http://<seaweedfs-host>:8181
+    warehouse: s3://<table-bucket-name>
+    credential: <access-key>:<secret-key>
+    s3.endpoint: http://<seaweedfs-host>:8333
+    s3.access-key-id: <access-key>
+    s3.secret-access-key: <secret-key>
+    s3.path-style-access: true
+```
+
 ### SQL Catalog
 
 The SQL catalog requires a database for its backend. PyIceberg supports PostgreSQL and SQLite through psycopg2. The database connection has to be configured using the `uri` property. The init_catalog_tables is optional and defaults to True. If it is set to False, the catalog tables will not be created when the SQLCatalog is initialized. See SQLAlchemy's [documentation for URL format](https://docs.sqlalchemy.org/en/20/core/engines.html#backend-specific-urls):