manus-skills/.kortix/opencode/skills/coding/clickhouse-architecture-advisor/rules/decision-ingestion-strategy.md
zhukang 1c7abd81d1 All 310 Manus skill-hub community skills as a Kortix marketplace registry
- 310 registry:skill items, 1528 files, 7 categories (hub tags)
- registry.json generated by @kortix/registry buildRegistry
- nested SKILL.md in sn-da-* renamed SUBSKILL.md (no phantom skills)
- provenance + licenses: SOURCES.md
2026-09-15 13:37:20 +08:00

2.2 KiB

title impact tags
Choose an ingestion strategy based on throughput, latency, and producer shape CRITICAL
ingestion
kafka
async_insert
real-time

Choose an ingestion strategy based on throughput, latency, and producer shape

Principle

Do not recommend a single ingestion pattern for every workload. The right approach depends on:

  • events per second
  • rows per insert
  • acceptable buffering latency
  • whether producers can batch
  • whether decoupling is required

Decision framework

Condition Recommended path Category
Producers can batch to 10K-100K rows and latency tolerance is moderate Direct inserts official
Producers send many small inserts and cannot batch effectively Async inserts official
Producers are bursty, many independent writers exist, or decoupling is needed Kafka engine + materialized view derived
Reliability, replay, and ingestion fan-out are primary concerns Upstream queue or log broker before ClickHouse field

Guidance

Recommendation: direct batched inserts

Use when the application can naturally batch inserts into healthy sizes.

Why The existing best-practices guidance already favors appropriately sized insert batches.

Official sources

Recommendation: async inserts

Use when producers emit many small writes and the application cannot easily batch.

Why Async inserts let ClickHouse buffer small writes server-side to reduce part pressure.

Official sources

Recommendation: Kafka engine + materialized view

Use when a queue-based, decoupled ingest path is needed.

Why This is typically the right design when multiple producers, burst handling, or replayability matter.

Category derived

Sources

Validation

  • Check average rows per insert
  • Check part creation rate
  • Check whether insert latency spikes correlate with small batch behavior