Data Archiving

Data archiving is the practice of moving inactive or rarely used data from primary storage to a secondary system where it can be securely retained for long-term access. Unlike backups, which are intended for recovery, archives serve as historical records.

Archived data:

• Remains accessible, but is not modified
• Is stored for years or even decades
• Is often subject to regulatory retention requirements

Common archive types include:

• Financial records
• Medical or legal documents
• Scientific datasets
• Project files from completed work
• System or user logs for audits

Open-E JovianDSS supports archiving through a combination of:

• Tiered storage design: Administrators can configure storage pools with different performance tiers, moving archive data to cost-efficient HDDs or JBODs, while keeping active data on fast SSDs.
• Snapshot-based retention: Snapshots can preserve read-only versions of datasets for specific dates or events, ensuring data can be reviewed even years later without modification.
• WORM-capable ZFS datasets: ZFS supports Write Once Read Many (WORM)-like configurations, allowing archived data to remain unchanged and protected from deletion or tampering.
• Compression and deduplication: Archival data often contains redundancies. JovianDSS optimizes space usage through inline compression and deduplication—especially effective for log files, documents, or templates.
• Remote/offsite replication: Archived datasets can be replicated to secondary storage in remote locations, enhancing long-term data protection and geographic resilience.

• Reduces costs on primary storage systems: Moving cold data off expensive high-performance drives frees space for critical workloads and delays costly infrastructure expansion.
• Supports regulatory compliance: Industries like healthcare, finance, or government must retain records for legal periods. Archiving ensures these datasets remain accessible and verifiable.
• Preserves historical knowledge: Archived records provide long-term access to business history, research results, project documentation, and other data that may gain relevance over time.
• Improves system performance: Reducing the volume of files and databases on active storage systems helps improve indexing, backup speed, and I/O responsiveness.
• Protects against accidental deletion: Archived data is stored separately, often with access restrictions, reducing the risk of overwrites, unauthorized changes, or file loss.

• Define clear archiving policies and retention periods: Determine what types of data qualify for archiving, how long they must be kept, and when they can be safely removed.
• Classify data before archiving: Identify valuable vs. redundant information to avoid unnecessary storage of irrelevant files and reduce clutter in long-term storage pools.
• Use immutable or WORM configurations when needed: For legal or audit-sensitive records, protect data with read-only permissions to prevent tampering or deletion.
• Label and document archives thoroughly: Include metadata, versioning info, and context so archived datasets remain understandable even years after their creation.
• Test retrieval workflows regularly: Periodically access archived data to ensure integrity, accessibility, and format compatibility for long-term usage.