Data Management Glossary
File Archiving
What is File Archiving?
File archiving is the process of preserving digital files for long-term data storage and retrieval. The goal of file archiving is to retain important files and documents in a secure, easily accessible, and cost-effective manner, while freeing up space on primary storage systems.
Manual file data management, backup and restore solutions, and dedicated file archiving systems are three ways to archive files. Manual file management moves files to a secondary storage location, such as a network share or external hard drive. Backup and restore solutions preserve files by creating snapshots of the data at regular intervals; snapshots can restore data in the event of data loss or corruption. Dedicated file archiving systems are specialized software solutions that are designed specifically for file archiving and provide features such as indexing, searching, and data retention policies.
File Archiving Challenges
File archiving reduces the risk of data loss, improves regulatory compliance, and reduces the costs associated with primary storage. Yet file archiving can present several challenges, including:
- Data Storage Costs: Storing large volumes of data for a long time can be expensive, especially if the data is stored on traditional storage solutions, such as tapes or hard disk drives.
- Scalability: As data volumes continue to grow, archiving solutions must be able to meet the increasing demand for storage capacity.
- Data Retrieval: Archived files are difficult to locate and retrieve if they are not properly indexed or if the index becomes corrupted.
- Data Retention: Organizations must ensure that their archiving solutions meet regulatory requirements for data retention, including data privacy and security laws.
- Data Integrity: Archived files must be preserved in their original format and remain readable over time, which requires proper data preservation and data migration strategies.
- Data migration: As archiving systems age or become obsolete, IT must migrate data to new systems, in particular cloud data migration, which can be time-consuming and complex.
- Integration with other systems: Archiving solutions must integrate with other systems, such as backup and restore solutions, to ensure streamlined access.
Standards-based Transparent Data Archiving
A true transparent data archiving solution creates literally no disruption, and that’s only achievable with a standards-based approach. Komprise Intelligent Data Management is the only standards-based transparent data archiving solution that uses Transparent Move Technology™ (TMT), which uses symbolic inks instead of proprietary stubs.
True transparency that users won’t notice
When a file is archived using TMT, it’s replaced by a symbolic link, which is a standard file system construct available in NFS, SMB, object store file systems. The symbolic link, which retains the same attributes as the original file, points to the Komprise Cloud File System (KCFS), and when a user clicks on it, the file system on the primary storage forwards the request to KCFS, which maps the file from the secondary storage where the file actually resides. (An eye blink takes longer.) This approach seamlessly bridges file and object storage systems so files can be archived to highly cost-efficient object-based solutions without losing file access.
Learn more about Komprise TMT for File Archiving
Latest Trends in File Archiving
File archiving is evolving from a compliance-driven practice into a strategic pillar for cost control and AI readiness.
1. Rising NAND Flash and Storage Costs
Enterprise SSD and NAND flash prices have surged due to AI demand and supply constraints. Some forecasts show:
- >50% increases in SSD pricing
- Significant cost pressure on all-flash arrays
As a result, organizations can no longer afford to keep inactive data on expensive flash storage.
2. Shift from Backup to Intelligent Archiving
Traditional archiving focused on compliance and retention. Modern archiving focuses on:
- Cost optimization
- Data lifecycle management
- Hybrid cloud integration
3. Convergence of Archiving and Tiering
File archiving is increasingly implemented via:
- Automated data tiering
- Movement of cold data to object storage or cloud
Over 70% of enterprise data is cold, yet often still sits on expensive primary storage.
4. AI and Data-Centric Architectures
Archived data is no longer “dead storage”. It is now:
- A source for AI training data
- A dataset for analytics and compliance
Why File Archiving is Critical in the Era of Expensive Flash
Flash storage delivers performance, but at a high cost. Flash is optimized for hot, active data. Archived data is typically:
- Inactive
- Rarely accessed
- Large in volume
Without archiving:
- Cold data accumulates on flash
- Storage costs increase dramatically
- Backup and DR systems become inefficient
File archiving:
- Moves cold data to lower-cost storage tiers
- Frees up primary storage capacity
- Extends the life of expensive flash investments
Modern storage strategies depend on archiving + data tiering working together
How File Archiving Supports AI and GenAI
File archiving plays an increasingly important role in AI pipelines.
1. Access to Historical Data
Archived data includes:
- Documents
- Logs
- Images and media
These datasets are critical for:
- Model training
- Retrieval-augmented generation (RAG)
- Compliance and audit use cases
2. AI Data Curation
Not all archived data is valuable. Challenges include:
- Duplicate files
- Outdated content
- Low-quality datasets (see ROT data)
AI requires: Curated, relevant datasets, not full archives
3. Cost-Efficient AI Pipelines
Without archiving and tiering:
- AI pipelines process excessive data
- Compute and storage costs increase
With proper archiving:
- Only relevant data is retrieved and processed
- AI efficiency improves
How Komprise Enhances File Archiving
Komprise modernizes file archiving by combining analytics, transparency, and automation.
Analytics-Driven Archiving
Komprise analyzes:
- File access patterns
- Age and usage
- Ownership and activity
Komprise ensures only cold, inactive data is archived
Transparent Move Technology (TMT)
- Files are archived to object or cloud storage
- Users and applications retain transparent access
No disruption, no broken links.
Intelligent Tiering for Cost Optimization
Komprise moves archived data off expensive primary storage so it can be efficiently stored on lower-cost storage tiers. This reduces storage costs while maintaining accessibility. It also reduces ransomware protection costs.
Global Metadatabase for AI and Retrieval
Provides a unified metadata index across all archived data and enables:
- Search
- Discovery
- AI data retrieval
The Komprise Global Metadatabase and Smart Data Workflows turn archives into AI-ready datasets. File archiving is no longer just about long-term storage.
The right approach to file archiving is now essential for:
- Controlling storage costs in a high-flash-cost environment
- Preparing unstructured data for AI
- Enabling efficient data retrieval across hybrid environments
What is file archiving?
File archiving is the process of moving inactive or infrequently accessed files to lower-cost storage while preserving access and integrity.
How is file archiving different from backup?
Backup = data protection and recovery. Archiving = long-term storage and cost optimization.
Why is file archiving important now?
Because rising NAND flash and storage costs make it too expensive to keep inactive data on primary storage.
How does file archiving reduce storage costs?
By moving cold data off high-cost storage (like flash) to lower-cost tiers such as object storage or cloud.
How does file archiving support AI?
It enables organizations to:
- Retain large historical datasets
- Curate and retrieve relevant data for AI pipelines
- Avoid processing unnecessary data
What is the relationship between archiving and tiering?
Modern file archiving is often implemented through intelligent data tiering, which automatically moves cold data to the appropriate storage tier.
How does Komprise improve file archiving?
Komprise uses analytics and automation to:
- Identify cold data
- Transparently archive it using TMT
- Optimize storage costs while enabling AI-ready data access