Zettabyte-Scale AI and Video Drive Long-Term Storage Rethink, Predicts Spectra Logic
Spectra Logic reports that surging data volumes from AI pipelines and video content are driving a shift towards object-based storage and tiered archival strategies. This aims to help streaming and IT professionals manage cloud egress fees, rising energy consumption, and data sovereignty requirements for zettabyte-level secondary storage.
Key Takeaways
- Global secondary storage demand is projected to reach zettabyte levels by 2030, driven by AI, machine-generated data, and retention needs.
- Object-based storage is replacing traditional file-based systems for large-scale archives due to better scalability and metadata-driven access.
- Tiering cold, infrequently accessed data to lower-power solutions reduces energy consumption and operational overhead.
- Complex cloud pricing models make long-term cost forecasting difficult, favoring transparent, predictable storage strategies.
- Access patterns, security (offline layers), and data sovereignty are critical considerations shaping hybrid archival designs.
Why It Matters
The explosion of AI data and video content is overhauling long-term storage, pushing organizations to re-evaluate reliance on public cloud for archival. Streaming services, often managing vast media libraries, face increasing pressure from cloud egress costs and energy consumption. This shift favors predictable, object-based storage and tiered solutions that balance performance, cost, and control, particularly as data retention periods extend over decades. Watch for increasing adoption of hybrid storage architectures that blend cloud flexibility with on-premise predictability for zettabyte-scale media archives.
Read full article at spectralogic.com