ClickHouseCalc CLICKHOUSECALC OLAP BROADSHEET · VOL. 2026 · RATES RETRIEVED 2026-11-12
VI · Bản Tiếng Việt

ClickHouseCalc Affiliate & Referral Disclosure: ClickHouseCalc (langfuse-llm-trace-storage) affiliate disclosure: clicking outbound /go/* partner links may earn a referral commission for ClickHouseCalc Editorial Desk at no additional cost to you. Read ClickHouseCalc Disclosure →

LLM OBSERVABILITY & EVALS // CLICKHOUSECALC BLUEPRINT

Langfuse v3 Self-Hosted ClickHouseCalc Sizing: ZSTD(9) Prompt & Completion Traces

ClickHouseCalc Editorial Desk · Public Vendor Rates Retrieved 2026-11-12

In our deterministic ClickHouseCalc model, Langfuse v3 stores verbose LLM system prompts, RAG context windows, and agent spans in ClickHouse where ZSTD(9) sliding windows deduplicate repeated prompt preambles across adjacent 8,192-row granules.

Verify Hostinger Specs for langfuse-llm-trace-storage via ClickHouseCalc → Compare UltaHost Options for langfuse-llm-trace-storage via ClickHouseCalc → Load Workload in ClickHouseCalc MergeTree Calculator →

ClickHouseCalc Compression, RAM & TCO Schedule for langfuse-llm-trace-storage

Ingestion Scale Raw Volume MergeTree NVMe Disk Node RAM & vCPU Modeled TCO Delta (2026-11-12)
10M LLM Spans/Day (90d · 14.8 GB/d) 1.33 TB Raw Prompts 125 GB NVMe (ZSTD-9 + 22% Buffer) 16 GB RAM / 4 vCPU ~$590/mo Managed SaaS vs $10.49/mo Hostinger KVM 4
50M LLM Spans/Day (365d · 74 GB/d) 27.0 TB Raw Prompts 2.45 TB Enterprise Disk 32–64 GB RAM / 12–16 vCPU ~$3,900/mo Managed SaaS vs $58–$79/mo UltaHost / InterServer
ClickHouseCalc Citation (langfuse-llm-trace-storage): Public vendor pricing retrieved 2026-11-12 (https://www.hostinger.com/vps-hosting, https://ultahost.com/vps-hosting); promotional and renewal rates change and must be verified at checkout.

ClickHouseCalc Langfuse v3 `observations` ZSTD(9) MergeTree Schema

CREATE TABLE langfuse.observations_compressed
(
  id String,
  trace_id String CODEC(ZSTD(3)),
  project_id LowCardinality(String),
  type LowCardinality(String),
  model LowCardinality(String),
  start_time DateTime64(3) CODEC(DoubleDelta, LZ4),
  input String CODEC(ZSTD(9)),
  output String CODEC(ZSTD(9)),
  prompt_tokens UInt32 CODEC(T64, LZ4),
  completion_tokens UInt32 CODEC(T64, LZ4),
  total_cost Decimal64(8) CODEC(ZSTD(3))
)
ENGINE = ReplacingMergeTree(start_time)
PARTITION BY toYYYYMM(start_time)
ORDER BY (project_id, type, toDate(start_time), id);

ClickHouseCalc MergeTree Production Checklist for langfuse-llm-trace-storage

  • Set `LANGFUSE_S3_EVENT_UPLOAD_ENABLED=true` against a local MinIO or S3 bucket so multi-megabyte base64 vision payloads bypass synchronous MergeTree column blocks.
  • Apply `CODEC(ZSTD(9))` specifically on `input` and `output` string columns to maximize dictionary compression on identical RAG prompt templates.
  • Place `(project_id, type, toDate(start_time))` at the front of `ORDER BY` so token-spend billing aggregations scan narrow date ranges.

ClickHouseCalc Engineering FAQ: langfuse-llm-trace-storage

Why does ClickHouseCalc model Langfuse v3 on ClickHouse MergeTree rather than PostgreSQL TOAST tables?

PostgreSQL TOAST storage incurs VACUUM bloat and row-level I/O amplification on 8 KB prompt JSON, whereas ClickHouse columnar storage aggregates `total_cost` and `model` columns without reading `input` or `output` `.bin` files.

How does ClickHouseCalc address data-residency requirements for private enterprise Langfuse v3 deployments?

Deploying Langfuse v3 and ClickHouse on a dedicated single-tenant VDS or bare-metal server keeps prompt histories within your selected regional datacenter (Singapore, Frankfurt, or US) under your own encryption keys.

Related ClickHouseCalc MergeTree Blueprints (langfuse-llm-trace-storage)