“We were impressed by the functionality of MetadataHub right from the start, and by how quickly new file formats were integrated for us.”
Carsten Schäuble
Head of IT - ZUSE Institut Berlin
Make metadata visible. Unlock potential.
MetadataHub
MetadataHub provides a comprehensive overview of data stored on NAS, in the cloud, and in object storage; it analyzes file and embedded metadata and makes unstructured data efficiently usable for search, analysis, AI, and workflows.
Find things faster. Understand them better.
How MetadataHub Brings Order to Your Data Landscape
MetadataHub analyzes, indexes, and links unstructured data regardless of its location—without altering your data. With intelligent search, tagging, and metadata analysis, accessing information
has never been easier.
The central layer for all your data sources
MetadataHub acts as a unified unstructured data layer across all your storage locations—whether on-premises, in the cloud, or in a hybrid environment.
Data doesn’t need to be moved: The Hub indexes it directly at its storage location, makes it searchable, and connects silos into a unified view. This saves end users and IT teams time and provides transparency across file servers, archive systems, object storage, and more.
Technical Fundamentals
- Supports SMB/CIFS, NFS, and S3 – vendor- and system-independent
- Metadata extraction from files, file systems, and embedded metadata
- Intelligent tagging via UI or API
- Automated data classification and filtering
- Fully scalable and container-based
- Self-service interface and REST API for automated workflows
Features that bring order and speed
Key Features of MetadataHub
From analysis and tagging to AI data provision: MetadataHub transforms unstructured data into actionable insights. Easy to integrate and intuitive to use—for data science, IT, and business departments alike.
Find relevant files faster
Context-based search filters large volumes of data by file type, age, attributes, and content. This reduces
your processing time.
Tagging Across the Entire Storage Infrastructure
Metadata can be assigned via the UI or API—regardless of the storage system. This creates a consistent information space.
Revitalizing Existing Archive Systems
Archive systems are fully indexed and searchable. Only filtered records need to be retrieved—saving both time and money.
Regardless of storage location and system
MetadataHub works with any storage system that can be connected via SMB, NFS, or S3. Every component is containerized.
Technically flexible. Designed for large volumes of data.
How MetadataHub Seamlessly Integrates into Your Infrastructure
With its modern architecture, standard protocols, and scalable design, MetadataHub can be seamlessly integrated into any enterprise environment.
System Architecture & Integration
MetadataHub is based on a containerized microservices architecture and can be flexibly integrated into any environment. It supports NAS, object storage, and cloud systems alike and indexes millions of files without requiring infrastructure changes. Search queries can be saved, automated, or transferred to third-party systems via API.
This creates structured data pipelines for analytics, AI, and compliance. At the same time, administrators retain full control over data access and analysis at all times.
Security and Management Features
- REST API, CLI, and WebUI for flexible operation
- Automated harvesting (metadata extraction)
- Metadata-based filters and search logic
- Integration with data science tools, AI, and orchestration
- Multi-tenant capability and scalable architecture
- Integration into legal hold and compliance workflows
What our customers say
MetadataHub Unlocks the Value of Unstructured Data
From research and government agencies to industry—MetadataHub is transforming data landscapes around the world.
Frequently Asked Questions
Everything you need to know about MetadataHub
Here you’ll find answers to the most important questions about architecture, search, tagging, integration, and performance. Ideal for organizations that want to use unstructured data more efficiently and make their storage landscape more transparent.
What is GRAU DATA's MetadataHub?
MetadataHub is a platform for cataloging, analyzing, and utilizing metadata across unstructured data. It collects and indexes metadata from NAS, object storage, and cloud systems, making data discoverable and ready for analysis, AI workloads, compliance, and operational workflows.
What problems does MetadataHub solve?
It brings transparency to unstructured data sets, reduces search times, improves data quality and governance, and enables automated workflows for data analysis and AI models—without requiring any changes to existing storage infrastructures.
What storage platforms and formats does MetadataHub support?
MetadataHub supports NAS shares, object storage (S3-compatible), and cloud storage systems. It analyzes and indexes metadata from a wide variety of file formats, including embedded metadata.
How does the indexing of large datasets work?
The solution processes millions of files using a containerized microservices architecture. This allows large volumes of data to be indexed efficiently without having to modify existing infrastructure or storage locations.
What metadata is collected?
MetadataHub captures both file system metadata (e.g., name, size, modification date) and embedded metadata from various formats (e.g., EXIF, XMP, document properties, application metadata) to create a comprehensive data profile.
How does MetadataHub help with compliance and governance requirements?
Centralized metadata indexing and analysis make it easy to implement retention policies, classification, and audit trails. Administrators maintain full visibility into data access and usage.
Can I save or automate search queries?
Yes. Search queries can be saved, run on a regular basis, or transferred to third-party systems via APIs to create automated processes or workflows.
How can the metadata hub be integrated into existing systems?
MetadataHub is based on a containerized microservices architecture and can be flexibly integrated into on-premises, hybrid, or cloud environments. APIs enable integration with external tools and platforms.
Does MetadataHub support AI-powered analytics?
Yes. High-quality data is the foundation for successful processing by AI. MetadataHub sifts through the vast amount of unstructured data to identify the right data for successful processing by AI.