---
title: "MetadataHub With Wasabi"
slug: "metadatahub-with-wasabi"
updated: 2026-06-25T16:44:27Z
published: 2026-06-25T16:44:27Z
canonical: "docs.wasabi.com/metadatahub-with-wasabi"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wasabi.com/llms.txt
> Use this file to discover all available pages before exploring further.

# MetadataHub With Wasabi

GRAU Data’s [MetadataHub](https://www.graudata.com/en/products/metadata-mining/metadata-hub/) is a platform and service that enables organizations to extract richer understanding from the metadata embedded in their unstructured documents, images, and other data sources. Acting as a unified hub, it consolidates, enhances, and adds context to metadata spanning an organization's entire data landscape, eliminating data silos through capabilities such as data cataloging, lineage tracking, and data quality monitoring, so that unstructured files and data assets become easily searchable and primed for AI use.

> The use of this application may result in significant data egress depending upon the type of additional optional extractors used to analyze the objects in a given bucket. For example, the MD5 extractor will need to egress the entire object in order to compute the MD5 sum of the object. Be sure to reach out to MetadataHub support, prior to running your metadata analysis, to confirm how it may impact your data egress from Wasabi.

## Requirements

- A Wasabi Hot Cloud Storage Account

## Configuring MetadataHub With Wasabi

The example below uses a test bucket containing 10 image files.

![Screenshot of Wasabi bucket UI titled test-bucket-metadatahub showing the bucket details and a table listing multiple image files (jpg) with columns for Name, Type, Last Modified, Size, and Actions; UI includes Create Folder and Upload Files buttons](https://cdn.document360.io/bef0a1ea-7768-4d5a-b520-c4fe2f7fafad/Images/Documentation/metadatahub-with-wasabi_page_0001_img_01.png)

## S3 Metadata

Optionally, to extract S3-specific metadata, register the S3 extractor for Wasabi before running the harvest task. Enable it in the Extractors panel when configuring the task.

![](https://cdn.document360.io/bef0a1ea-7768-4d5a-b520-c4fe2f7fafad/Images/Documentation/image-Z1AFVTQJ.png)
  - A Wasabi Bucket (see [Creating a Bucket](https://docs.wasabi.com/docs/working-with-buckets-and-objects#creating-a-bucket))
  - Access & secret key pair

> Be sure to note your bucket name, storage region URL, and Access & Secret Key, as you will need these for later steps.
  - Access to the MetadataHub Registry
  - A valid MetadataHub License
  - Docker (Compose) & s3fs installed
  1. Create a new directory with the following structure.
    - `.credentials` —Stores the S3 access/secret key
    - `.env` —Stores configuration values for the Compose file
    - `compose.yml` —Defines the MetadataHub services
    - `data/test-bucket-metadatahub` —Mount point for the Wasabi bucket
  2. Mount the S3 test bucket using **s3fs** so MetadataHub Core can access the files.

> This configuration example discusses the use of Wasabi's eu-central-2 storage region. Use the region your bucket is located in. For a list of regions, see [Service URLs for Wasabi's Storage Regions(opens in new tab)](https://docs.wasabi.com/docs/what-are-the-service-urls-for-wasabi-s-different-storage-regions).

```plaintext
s3fs \     
    test-bucket-metadatahub \     
    ./data/test-bucket-metadatahub/ \    
    -o subtype=s3 \     
    -o use_path_request_style \     
    -o ro \     
    -o fsname=https://s3.eu-central-2.wasabisys.com/test-bucket-metadatahub \     
    -o endpoint=s3.eu-central-2.wasabisys.com \     
    -o url=https://s3.eu-central-2.wasabisys.com \     
    -o passwd_file=./credentials \     
    -o allow_other \     
    -o umask=0022 \     
    -o noexec
```
  3. Configure `compose.yml` with a minimal MetadataHub setup. This includes one Core, one Hub, and a Postgres database. Fill in the required values in `.env` and start the services.

```plaintext
services:
  mdh-wasabi-core:
    image: registry.metadatahub.de/main/core:3.8
    container_name: mdh-wasabi-core
    depends_on:
      mdh-wasabi-db:
        condition: service_healthy
    environment:
      MDH_CONFIG_DATABASE_HOST: mdh-wasabi-db
      MDH_CONFIG_DATABASE_PASSWORD: ${MDH_CONFIG_DATABASE_PASSWORD}
      MDH_CONFIG_CREDENTIAL_USER: ${MDH_CONFIG_CREDENTIAL_USER}
      MDH_CONFIG_CREDENTIAL_ADMIN: ${MDH_CONFIG_CREDENTIAL_ADMIN}
      MDH_CONFIG_SERVER_APP_SSL: false
      MDH_CONFIG_SERVER_APP_SSL_VERIFY: NO_VERIFY
      MDH_CONFIG_HARVESTER_SHARE_O_NAME: test-bucket-metadatahub
      MDH_CONFIG_HARVESTER_SHARE_O_HOST: /home/mdh/wasabi/data/test-bucket-metadatahub
      MDH_CONFIG_INSTANCE_NAME: mdh-wasabi-core
      MDH_CONFIG_DATABASE_NAME: wasabi-core
    volumes:
      - ./data/test-bucket-metadatahub:/var/opt/mdh-core/harvester/filesystem/test-bucket-metadatahub:ro

  mdh-wasabi-hub:
    image: registry.metadatahub.de/main/hub:3.8
    container_name: mdh-wasabi-hub
    environment:
      HUB_TIMEZONE: Europe/Berlin
      HUB_ADMIN_NAME: ${HUB_ADMIN_NAME}
      HUB_ADMIN_FIRST_NAME: ${HUB_ADMIN_FIRST_NAME}
      HUB_ADMIN_LAST_NAME: ${HUB_ADMIN_LAST_NAME}
      HUB_ADMIN_EMAIL: ${HUB_ADMIN_EMAIL}
      HUB_ADMIN_PASSWORD: ${HUB_ADMIN_PASSWORD}
      HUB_SSL: false
      HUB_SSL_VERIFY: NO_VERIFY
      HUB_HTTP_COOKIE_SECURE: false
    volumes:
      - mdh-wasabi-hub-db:/app/database
    ports:
      - 127.0.0.1:9001:8000

mdh-wasabi-db:
  image: postgres:18
  container_name: mdh-wasabi-db
  environment:
    POSTGRES_DB: postgres
    POSTGRES_USER: metadatahub
    POSTGRES_PASSWORD: ${MDH_CONFIG_DATABASE_PASSWORD}
  healthcheck:
    test: ["CMD-SHELL", "pg_isready -U metadatahub -d postgres"]
    interval: 5s
    timeout: 3s
    retries: 5
    start_period: 10s
  volumes:
    - mdh-wasabi-postgres-db:/var/lib/postgresql

volumes:
  mdh-wasabi-hub-db:
  mdh-wasabi-postgres-db:
```
  4. Open the Hub URL in your browser and log in. Use the credentials set by HUB_ADMIN_NAME / HUB_ADMIN_PASSWORD.

![](https://cdn.document360.io/bef0a1ea-7768-4d5a-b520-c4fe2f7fafad/Images/Documentation/image-114WVRP1.png)
  5. To add the Core, navigate to **Instances**.
  6. Select **Actions**.
  7. Click **Add**.
  8. To create a harvest task, click **Menu**.
  9. Click **Harvest**.
  10. Click **Tasks**.
  11. Click **Actions.**
  12. Click **Add Task**.
  13. In the Shares panel, select the test-bucket-metadatahub share. This creates a new harvest task called Wasabi that will extract files from the bucket.

![](https://cdn.document360.io/bef0a1ea-7768-4d5a-b520-c4fe2f7fafad/Images/Documentation/image-BWA8ZDJD.png)

![](https://cdn.document360.io/bef0a1ea-7768-4d5a-b520-c4fe2f7fafad/Images/Documentation/image-AHY34IDX.png)

![Screenshot of MetadataHub web UI showing a tasks table with a row for a task named Wasabi. Table headers visible include Type, Status, Name, Next, Started At, Updated At, Time, Files; the Wasabi row shows a finished status and 10 files.](https://cdn.document360.io/bef0a1ea-7768-4d5a-b520-c4fe2f7fafad/Images/Documentation/metadatahub-with-wasabi_page_0006_img_01.png)