Data Management Glossary
Unstructured Data Storage
What is Unstructured Data Storage?
Unstructured data storage is the storage of data that does not adhere to a predefined data model or schema. Unlike structured data, which fits neatly into tables with rows and columns, unstructured data lacks a specific organization and may include various file types, such as text documents, images, videos, audio files, emails, social media posts, and more.
Read the article: Here’s How to Take Control of Unstructured Data
Gartner on unstructured data storage
Each year Gartner publishes the Magic Quadrant for Distributed File Systems and Object Storage.
Gartner defines distributed file systems and object storage as software and hardware appliance products that offer object and distributed file system technologies for unstructured data. Their purpose is to store, secure, protect and scale unstructured data with access over the network using file and object protocols, such as Amazon Simple Storage Service (S3), Network File System (NFS) and Server Message Block (SMB).
Gartner also has a Primary Data Storage Magic Quadrant, as summarized in this Blocks & Files article.
Common requirements for unstructured data storage
- Flexibility: Unstructured data storage systems are flexible and can accommodate various types of data without requiring predefined schemas. This flexibility allows organizations to store and manage diverse data types efficiently.
- Scalability: Unstructured data storage solutions are often designed to scale easily, allowing organizations to handle massive volumes of data as their storage requirements grow over time.
- Indexing and Search: Effective management of unstructured data involves indexing and search capabilities to quickly locate and retrieve specific information within large datasets. This may involve metadata tagging, full-text search, and other techniques to facilitate data discovery. See unstructured data classification.
- Object Storage: Object storage is a common approach to storing unstructured data, where each piece of data is stored as an object with a unique identifier and metadata. Object storage systems provide scalability, durability, and accessibility for large-scale unstructured data environments.
- Cloud Storage: Many organizations leverage cloud storage services for unstructured data storage due to their scalability, reliability, and cost-effectiveness. Cloud providers offer a range of storage options, including object storage, file storage, and content delivery networks (CDNs), to accommodate different types of unstructured data.
- Data Governance and Security: Managing unstructured data requires robust data governance practices to ensure compliance, data security, and privacy protection. This may involve implementing access controls, encryption, data classification, and audit trails to safeguard sensitive information.
Effective storage and unstructured data management are essential for organizations to derive insights, make data-driven decisions, and unlock the value of their data assets.
Unstructured Data Storage Vendors
Many vendors offer solutions for storing unstructured data, each with its own set of features, capabilities, and pricing models. Here are some notable vendors in the unstructured data storage space:
- Amazon Web Services (AWS): Amazon Simple Storage Service (S3) (AWS S3) is a highly scalable object storage service designed for storing and retrieving any amount of data. It is commonly used for unstructured data storage and offers features such as versioning, lifecycle management, and security features. Learn more about Komprise for AWS.
- Microsoft Azure: Azure Blob Storage provides scalable, cost-effective storage for unstructured data. It offers tiered storage options, access controls, and integration with other Azure services for data analytics and processing. Learn more about Komprise for Azure.
- Google Cloud Platform (GCP): Google Cloud Storage is a scalable object storage solution suitable for storing unstructured data. It provides features such as versioning, lifecycle management, and integration with other GCP services. Learn more about Komprise for Google.
- IBM: IBM Cloud Object Storage: IBM offers Cloud Object Storage, a scalable, secure, and durable object storage service. It is designed to support large-scale unstructured data storage and offers features such as encryption, access controls, and global data distribution. Learn more about Komprise for IBM.
- Dell: Dell EMC Isilon, now Dell PowerScale, is a scale-out network-attached storage (NAS) platform designed for storing and managing large volumes of unstructured data. It offers high performance, scalability, and multi-protocol support for various data types. Learn about Komprise Elastic Data Migration for Isilon.
- NetApp: NetApp StorageGRID is an object storage solution from NetApp that enables organizations to store, manage, and protect unstructured data at scale. It offers features such as geo-distribution, data tiering, and policy-based management. Learn more about Komprise for NetApp.
- Pure Storage: Pure Storage FlashBlade is a scalable, all-flash storage platform designed for unstructured data workloads. It offers high performance, simplicity, and native support for file, object, and analytics workloads.
HPE (Hewlett Packard Enterprise): For years it has been HPE Nimble Storage, which offers a range of storage solutions, including Nimble Storage dHCI and Nimble Storage All Flash Arrays, suitable for storing unstructured data. HPE now resells VAST Data solutions as HPE File Services.
Qumulo: Qumulo’s Scale Anywhere™ platform is a 100% software solution for hybrid enterprises to efficiently store and manage file & object data at the edge, in the core, and in the cloud
These are some examples of vendors providing solutions for unstructured data storage.
Optimize unstructured data storage with Komprise
Komprise Intelligent Data Management frees you to analyze, mobilize, and access the right file and object data across clouds without shackling your data to any unstructured data storage vendor. Komprise helps enterprise customers optimize data storage costs by right-sizing and right-placing
data, while making it easy for users to unlock data value with smart data workflows.
What are the Latest Trends in Unstructured Data Storage?
Unstructured data storage is evolving rapidly as organizations adapt to AI, cloud, and massive data growth.
1. Explosive Data Growth
Unstructured data now represents 80–90% of enterprise data. Growth is driven by:
- AI and machine learning
- IoT and edge devices
- Rich media (video, imaging, genomics, etc.)
2. Shift to Hybrid and Multi-Cloud Storage
Data is increasingly distributed across:
- On-prem NAS systems
- Public cloud object storage
- Cloud file services
As a result, storage is no longer centralized, making management and visibility more complex.
3. Rising Storage and Cloud Costs
According to the Komprise State of Unstructured Data Management report, enterprise IT organizations spend 30%+ of IT budgets on data storage. Key data storage cost drivers:
- Flash and high-performance storage
- Cloud storage and egress fees
- Backup and disaster recovery overhead
4. AI-Driven Data Requirements
Unstructured data is the primary fuel for AI. Organizations must:
- Find relevant datasets
- Filter noise (redundant, obsolete data)
- Prepare data for AI pipelines
5. Intelligent Data Tiering and Lifecycle Management
Enterprises are adopting:
- Automated intelligent data tiering (hot → warm → cold)
- Policy-based data management and movement
Goal: Reduce costs while maintaining access
What are the Challenges of Unstructured Data Storage?
Modern storage environments introduce several key challenges:
- Lack of visibility (especially across data silos): Difficult to know what data exists and where
- Data sprawl: Data spread across silos and environments
- Cost inefficiency: Cold data stored on expensive infrastructure
- Limited metadata: Makes search, retrieval, and AI use difficult
- Scalability issues: Billions of files across petabyte-scale environments
Without proper data management, unstructured data becomes a cost and risk liability instead of an asset.
How Does Unstructured Data Storage Impact AI and GenAI?
Unstructured data plays a critical role in AI and generative AI (GenAI). AI models depend heavily on:
- Documents
- Images
- Audio and video
However, much of this data is unlabeled, duplicated, or irrelevant. (ROT data). The challenge is AI systems often:
- Process too much data
- Lack context about data quality and relevance
This results in:
- Higher compute costs
- Slower pipelines
- Lower-quality AI outputs
The shift: AI Data Retrieval and Curation
Modern architectures prioritize:
- Finding the right data (not all data)
- Filtering and curating datasets before AI processing
This makes metadata, data classification and data discovery essential components of unstructured data storage strategies.
How Komprise Enhances Unstructured Data Storage
Komprise transforms unstructured data storage into an intelligent, analytics-driven data platform.
Global Metadatabase (Unified Metadata Layer)
Komprise creates a global index of metadata across all storage:
- Billions of files across NAS, cloud, and object storage
- Fast search and filtering
- Unified visibility across environments
- Analytics-Driven Intelligent Data Tiering
Komprise enables:
- Identification of cold vs hot data
- Policy-based movement of inactive data to lower-cost storage
- Data workflows for data ingestion, PII detection and metadata extraction
Result:
- Reduced storage, backup and cloud costs
- Optimized use of flash and cloud (see Flash Stretch)
With Transparent Move Technology (TMT):
- Data is moved without breaking access
- Users continue to access files as if they never moved
No disruption to applications or workflows.
Komprise helps prepare unstructured data for AI by:
- Filtering redundant and low-value data
- Identifying high-value datasets
- Delivering curated data to AI pipelines
Komprise shifts unstructured data storage from:
“Where do I store my data?”
to:
“How do I make my data usable, cost-efficient, and AI-ready?”
What is unstructured data storage?
Unstructured data storage refers to systems and technologies used to store data that does not fit into traditional databases, such as files, images, videos, and documents.
Why is unstructured data storage challenging?
Because of its scale, lack of structure, and distribution across hybrid and multi-cloud environments.
How does unstructured data storage impact costs?
Storing large volumes of inactive data on high-performance storage significantly increases infrastructure and cloud costs.
What is the role of metadata in unstructured data storage?
Metadata provides context (e.g., owner, usage, age), enabling search, governance, and AI-driven insights.
How does unstructured data storage relate to AI?
Unstructured data is the primary input for AI and GenAI, but must be discovered, filtered, and curated to be useful.
How does Komprise improve unstructured data storage?
Komprise provides global visibility, analytics, intelligent tiering, and data curation to optimize costs and prepare data for AI.