What is Storage Tiering and How Does it Differ from Caching?

Definition
Storage tiering organizes data across storage classes with different cost and access characteristics based on access patterns. Hot tier uses fast, expensive storage for frequently accessed data. Cold tier uses slow, cheap storage for rarely accessed data. Warm tier sits between.
The Core Problem
Storage costs and access speeds are inversely related. Fast storage (SSD, NVMe) costs $0.08-0.15/GB/month. Slow storage (archive, tape) costs $0.004/GB/month. A 20x cost difference. Most data follows the 80/20 rule: 80% of accesses go to 20% of data. Paying premium storage prices for the rarely accessed 80% wastes significant budget. Tiering automatically moves data to appropriate storage classes, optimizing the cost and performance balance.
Tiering vs Caching
Caching and tiering seem similar but solve different problems. Caching is about read latency. Data exists in slow storage and is temporarily copied to fast storage for speed. Cache misses hit the slow backend. Data is never deleted from primary storage. Tiering is about storage cost. Data is moved (not copied) between storage classes. The original location becomes empty. Access latency varies based on current tier. The key difference: with caching, all data lives in one tier with a fast cache in front. With tiering, data lives in exactly one tier at a time, selected based on access patterns.
💡 Key Insight: Caching optimizes for latency (speed). Tiering optimizes for cost (storage expense). Many systems use both: tiering to reduce storage costs, caching to reduce access latency for frequently accessed items in any tier.
The Three Tier Model
Hot tier provides immediate access with sub-millisecond latency. Used for active data accessed multiple times per day. Highest storage cost but no retrieval fees. Warm tier provides access within seconds to minutes. Used for data accessed occasionally, perhaps once per week or month. Lower storage cost with small retrieval fees. Cold tier may require hours for retrieval. Used for compliance archives, disaster recovery, and legal hold data. Lowest storage cost with significant retrieval fees. Some systems add frozen tier with 12+ hour retrieval for long term retention.
When Tiering Matters
Tiering becomes economically significant when: total storage exceeds 10TB+, data has clear age based access patterns (older data accessed less), access patterns are predictable, and the organization can tolerate retrieval delays for cold data. For a 100TB dataset where 80% is cold, moving cold data from hot to archive tier saves roughly $8,000/month. The complexity of tiering automation pays for itself quickly at scale.

💡 Key Takeaways

✓Storage tiering moves data between storage classes based on access patterns - hot (fast/expensive) to cold (slow/cheap) with 20x cost difference

✓Tiering differs from caching: tiering moves data to reduce costs, caching copies data to reduce latency

✓Three tier model: hot (sub-ms latency, no retrieval fee), warm (seconds, small fee), cold (hours, significant fee)

✓Tiering pays off at 10TB+ with clear access patterns - 100TB dataset with 80% cold saves roughly $8,000/month

📌 Interview Tips

1Explain the 80/20 access pattern rule and how it justifies tiering - 80% of accesses go to 20% of data

2When asked about caching vs tiering, clarify that caching optimizes for latency while tiering optimizes for storage cost

3Mention the break even point for tiering complexity - typically 10TB+ with predictable access patterns

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