Storage Choices for ClickHouse and OLAP Workloads: NVMe, HDD, or Emerging PLC Flash?

Hook: Your ClickHouse cluster is fast — but is your storage the bottleneck?

Architects and DevOps teams deploying ClickHouse for real-time analytics face a repeated trade-off: high throughput and low latency for queries versus durable, cost-effective capacity for petabyte-scale retention. Choosing between NVMe SSDs, HDDs, or the emerging promise of PLC flash (predicted by SK Hynix and others) is now a strategic decision that affects performance, lifecycle cost, and operational risk.

Executive summary — what to choose, in one page

• Hot OLAP tiers / high-concurrency queries: NVMe (enterprise) — lowest latency, highest IOPS, best for MergeTree heavy workloads and materialized views.
• Cold, high-capacity retention: HDD or PLC (once proven in-datacenter) — HDD for cheapest $/GB today; PLC could displace QLC for cheaper SSD capacity later in 2026–2027.
• Hybrid strategy: NVMe for write/merge/cache + HDD/PLC for long-term storage and infrequent scans. Use ClickHouse features (compression, TTL, tiered storage) to optimize costs.
• Durability & endurance: Budget for SSD endurance (DWPD/TBW) to cover ClickHouse merge write amplification. PLC promises capacity gains but lower P/E cycles — plan accordingly.

Why storage choice matters more than compute for OLAP in 2026

ClickHouse and similar OLAP engines are optimized for columnar reads and compression. While CPU and memory are visible knobs, I/O characteristics — sequential throughput, random-read latency, and background write amplification from merges — determine real-world QPS and maintenance windows.

Two trends in 2025–2026 turbocharge the importance of storage planning:

• Cloud and on-prem workloads increasingly push PB-scale retention as businesses keep raw telemetry longer for ML use cases.
• Flash supply pressures and new cell technologies (PLC) promise cheaper SSD bytes, but bring new endurance and reliability trade-offs.

Storage media primer for OLAP architects (2026 context)

NVMe SSDs (enterprise)

Where they shine: ultra-low latency (tens of microseconds), high IOPS, sustained throughput for parallel queries, excellent random-read performance. Ideal for ClickHouse hot data, merges, and replicated shards that need low tail latency.

Durability & metrics: specify DWPD (drive writes per day) or TBW. Enterprise NVMe often targets 0.3–3 DWPD depending on the class (read-optimized vs mixed-use).

HDD (enterprise hard drives)

Where they shine: best $/GB for capacity (approx ranges below). Good for large, sequential scans and cold OLAP tiers. Higher latency (single-digit milliseconds), low IOPS for random reads.

Durability & metrics: MTBF/AFR and sustained throughput matter. HDDs are mechanically fragile for random I/O but robust for append-heavy workloads and cold storage.

PLC flash (programmable / penta-level cell; emerging)

What PLC is: a successor to QLC where cells store more bits (5+ levels), yielding higher density and lower $/GB. SK Hynix in late 2025 introduced a cell-chopping approach that improves viability of PLC by altering cell charge management to reduce error rates and improve read margins.

Where it could fit: read-heavy, high-capacity SSD tiers where cost matters more than write endurance. Think cold tier SSDs in datacenters and cloud-local capacity drives.

Caveat: as of early 2026, PLC prototypes and first-generation products require conservative adoption. Endurance and firmware maturity lag TLC/QoL SSDs — plan for gradual integration and validation.

Key metrics that determine ClickHouse performance and TCO

• Cost per GB (approx, 2026):
  • Enterprise HDD: ~$0.02–$0.05/GB
  • Enterprise NVMe SSD (dense TLC/QLC): ~$0.10–$0.30/GB (wide range by endurance & interface)
  • PLC (forecast early deployments): projected $0.05–$0.12/GB — competitive with HDD on some metrics but with flash speed advantages
• Latency: NVMe microseconds; HDD milliseconds — orders of magnitude gap that matters for interactive queries.
• IOPS: NVMe: 10k+ random IOPS per drive; HDD: 100–300 IOPS.
• Endurance: Measured in DWPD or TBW. ClickHouse background merges can multiply writes — model expected daily writes before choosing SSD class.

Quantifying endurance: a worked example

Plan with numbers. Suppose a cluster ingests 5 TB of raw data per day. ClickHouse MergeTree merges and compactions produce write amplification — conservative factor here is 1.5–3.0 depending on schema, compressibility, and merge frequency.

1. Ingest: 5 TB/day
2. Merge amplification: 2x => total writes = 10 TB/day
3. Monthly writes ≈ 300 TB; yearly writes ≈ 3.6 PB

If you pick an NVMe with 3 DWPD and 50 TB capacity, daily write budget = 150 TB (3 × 50 TB). That drive can sustain 10 TB/day easily. If you choose a QLC/PLC drive with 0.1 DWPD, daily write budget = 5 TB — barely covering the raw ingestion and not the amplified merges.

Actionable rule: dimension SSD endurance against expected merged writes (ingest × amplification). If the budget fails, select higher-endurance SSDs, increase overprovisioning, or shift merges to a cheaper tier.

Architecture patterns: where each medium fits

1) All-NVMe hot cluster

Use when sub-10ms tail latency and high concurrency are top priorities (ad networks, real-time dashboards). Expect higher $/GB but simplified performance tuning. Recommended for indexes, primary partitions, and frequently-queried recent data.

• Configuration tips: enterprise NVMe with >1 DWPD, RAID 1/10 or distributed replication (ClickHouse Replication), large L2ARC-style cache isn't necessary if compute nodes have big memory pools.

2) NVMe + HDD (hybrid) — current practical sweet spot

Keep a hot NVMe tier for writes and merges, then offload cold parts to HDD. ClickHouse supports data movement via TTL and table-level storage policies, enabling automatic tiering.

• Use NVMe for MergeTree active partitions and for query caches.
• Use HDD RAID/erasure-coded arrays for bulk storage with occasional full-table scans.
• Compress aggressively with ZSTD and tune index_granularity to reduce random I/O.

3) NVMe + PLC (emerging hybrid)

When PLC products prove endurance in the field (expected rolling adoption in 2026–2027), they will slot between HDD and NVMe in $/GB and latency. For read-heavy cold SSD tiers, PLC can reduce scan latency vs HDD while keeping cost down.

Adopt PLC initially as a second-tier SSD: validate with extended soak tests and firmware updates, and run realistic ClickHouse merges to measure device wear.

Operational recommendations — how to validate and deploy

Benchmark realistically

• Use fio profiles that mimic ClickHouse IO: mixed sequential writes (large blocks) for ingestion and random reads (4K–64K) for query patterns.
• Run long-duration wear tests for PLC/QLC drives (weeks) to observe slow-developing firmware issues and performance cliffs under GC.

Monitor the right metrics

• SSD SMART attributes (percentage used, media errors)
• Queue depth and tail latency percentiles (p95/p99)
• ClickHouse metrics: background merges, parts count, compress ratio, read amplification

Protect against write storms

Design buffer layers: Kafka for ingestion smoothing, intermediary NVMe write buffers with persistent queues, or write-optimized partitions to avoid sudden mass merges.

Use storage policies and TTL

ClickHouse supports table-level storage policies that let you automatically move older parts to cheaper media. Implement policies that move data after a retention window and trigger manual rebalances during low-traffic periods.

Datacenter-level considerations

• Power & cooling: NVMe density increases rack power draw. PLC and QLC add capacity density but don’t always reduce power per GB; check vendor PUE impacts.
• Warranty & RMA: Enterprise SSD warranties often tied to TBW. Ensure procurement SLAs cover realistic OLAP wear patterns.
• Firmware support: New PLC controllers require matured firmware for latency stability. Plan a staged rollout and firmware regression testing.
• Cloud procurement: Evaluate local ephemeral NVMe vs network-attached (EBS/Azure Disk). Local NVMe gives lowest latency but complicates node replacement and replication.

SK Hynix PLC: realistic timeline and impact

SK Hynix’s approach of “chopping cells in two” (announced in late 2025) is a technical attempt to stabilize cell behavior at higher density. The 2026 reality is:

• First-generation PLC SSDs will target read-heavy applications and cold tiers where lower DWPD is acceptable.
• Adoption in critical OLAP hot tiers is unlikely immediately — firmware, controller optimization, and long-term field data are required.
• By late 2026–2027, PLC could materially reduce $/GB for SSD tiers, forcing architects to revisit two-tier SSD (NVMe hot + PLC cold-SSD) topologies.

"PLC is promising for capacity economics, but treat initial deployments as experimental until endurance & controller stacks mature."

Decision matrix: pick by scenario

Startup / Proof-of-Concept (up to 50 TB)

• Recommendation: Mixed NVMe (for recent data) + cloud object storage snapshots for older data. Use managed ClickHouse or cloud instances with local NVMe to keep latency low.

Enterprise analytics (50 TB – 2 PB)

• Recommendation: NVMe for active partitions (1–3 DWPD), HDD for bulk retention. Prepare for phased PLC trials for warm SSD tiers once vendor firmware is validated.

Hyperscale (multi-PB)

• Recommendation: Tiered approach — NVMe write/merge tier; PLC/warm SSD tier for frequent scans; HDD/erasure-coded cold tier. Strongly model TBW and lifecycle replacement cycles.

Checklist for procurement teams

1. Model write amplification from ClickHouse merging and multiply by ingest to calculate required TBW.
   
2. Ask vendors for endurance in DWPD and realistic enterprise workloads (not just synthetic specs).
   
3. Plan a phased PLC evaluation with soak tests, error rate monitoring, and firmware regression gates.
   
4. Design storage policies in ClickHouse that allow transparent tiering (TTL + policy).
   
5. Include replacement schedules and spare inventory in TCO models; SSDs fail differently than HDDs — plan for bit- vs mechanical-fail recovery.
   

Practical tuning tips for ClickHouse and storage

• Reduce index_granularity only when queries demand higher precision; bigger index_granularity lowers index size and reduces random reads.
• Enable aggressive compression codecs (ZSTD level 3–5) for archival parts to save GB and write bandwidth.
• Spread MergeTree merges over time via merge_scheduler settings to avoid sustained write spikes that wear SSDs.
• Use TTL moves during off-peak windows to reduce compaction impact on hot tiers.

Future predictions (2026–2028)

• PLC SSDs will appear in vendor catalogs in 2026; enterprise adoption will scale in 2027 as firmware stabilizes.
• Cost per SSD terabyte will compress, making multi-tier SSD architectures more attractive vs HDD-only cold tiers.
• ClickHouse adoption (backed by strong 2025–2026 funding and ecosystem growth) will push more vendors to certify PLC and QLC devices specifically for OLAP workloads.

Actionable takeaway (do these this week)

1. Run a write-amplification model for your ClickHouse tables and calculate required TBW for a 3-year lifespan.
2. Benchmark a candidate NVMe and a candidate QLC/PLC drive with fio using ClickHouse-like workloads (sequential large writes + random 4K reads) for at least 7–14 days.
3. Implement a tiered storage policy in a staging cluster: NVMe hot, HDD (or PLC when validated) warm, object/cold for archive.
4. Document RTO/RPO and warranty terms for SSDs; plan spare capacity and replacement windows into procurement.

Final thoughts

There’s no single “best” storage medium for ClickHouse OLAP: the right answer blends performance, durability, and cost. In 2026, NVMe remains the default for hot OLAP tiers; HDDs still hold ground for raw capacity. PLC from SK Hynix and others is exciting and will likely shift architectures toward more SSD-based tiering — but treat early PLC runs as conservatively as you would any new silicon.

Call to action

Need a tailored storage-sizing worksheet or a ClickHouse tiering proof-of-concept? Download our free ClickHouse storage checklist and cost model or contact our team at tecksite for a paid evaluation — we’ll help you map ingestion, merge behavior, and endurance into a 3-year procurement plan.

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