Sound familiar?
- ▸ MergeTree compaction storms on a busy ReplacingMergeTree table — final-modifier SELECTs are slow, you considered switching to CollapsingMergeTree but changing the write pipeline isn't free, and you need a real recommendation.
- ▸ ClickHouse Cloud quote just landed and the per-second-billing math doesn't obviously beat your reserved-instance EC2 spend — you need an honest TCO model, not the vendor's.
- ▸ Sharding-key decision looming on a new fact table — picking wrong creates a full data rewrite later, and you want a second pair of eyes on the proposal before committing.
JusDB ClickHouse consultants give you written, sized, defensible decisions from production deployments. Book an architecture review →
Strategic advisory — not execution
ClickHouse Consulting Services
In short: ClickHouse consulting is strategic advisory delivered as written decision documents — MergeTree-family selection, projection vs materialized-view strategy, sharding-key and replication design, ClickHouse Keeper topology, ingestion architecture, and Cloud-vs-self-managed economics. You need it before committing to a sharding key, signing a Cloud quote, or scaling a deployment.
MergeTree-family selection, projection and MV strategy, ClickHouse Keeper topology, sharding decisions, and the Cloud-vs-self-managed economics — delivered as written decision documents. See the ClickHouse hub for the broader services overview.
What our ClickHouse consulting covers
Each deliverable is a written decision document, sized topology proposal, or costed trade-off analysis.
MergeTree Family Selection
MergeTree vs ReplicatedMergeTree vs Replacing/Collapsing/Summing/AggregatingMergeTree — chosen based on your write semantics (append, upsert, fact-update) and read pattern.
Projection vs MV Strategy
Where projections fit (same-table ad-hoc acceleration) vs where materialized views fit (fan-out to differently-shaped targets) — mapped from your slow-query log.
Sharding & Replication
Sharding-key selection (the irreversible decision), Distributed-over-Replicated layout, replica placement across racks/AZs, and the sharding-vs-projection trade-off.
Cloud vs Self-Managed
ClickHouse Cloud vs self-managed-on-K8s-or-EC2 economics, with per-second-billing vs reserved-instance modeling against your actual concurrency and growth.
Keeper & Coordination
ClickHouse Keeper vs ZooKeeper decision for new deployments, sizing for replication-task QPS, and the migration story for existing ZooKeeper fleets.
Ingestion Architecture
Kafka engine, S3 engine, RabbitMQ engine, native HTTP, Flink connector, Vector — chosen by freshness SLA, exactly-once requirements, and existing data infrastructure.
TTL & Storage Tiering
TTL-move-to-disk, S3 cold tier, JBOD volume strategy, and the operational rules for keeping hot working-set on NVMe while archiving cold partitions to object storage.
How a ClickHouse consulting engagement is shaped
1–2 weeks
Architecture Review
Deliverable
Topology recommendation, current-state risk register, MergeTree-variant audit, projection/MV sanity check, sized remediation roadmap.
When to pick this
Running ClickHouse already and want a second-opinion audit before scaling or signing a Cloud commitment.
1 week
Engine Decision
Deliverable
ClickHouse vs StarRocks vs Druid vs Pinot decision matrix with TCO model and per-engine risk profile.
When to pick this
Before committing to a real-time OLAP engine — head off the migration cost of choosing wrong.
1 week
Migration Strategy
Deliverable
Risk-graded migration plan — Snowflake → ClickHouse, PostgreSQL → ClickHouse, or self-managed → Cloud — with cutover sequence and rollback gates.
When to pick this
Before committing to any operationally significant ClickHouse migration.
2–3 weeks
Greenfield Design
Deliverable
Topology spec, capacity model, sharding-key decision, MergeTree-variant layout, ingestion pipeline design, security baseline, ops runbook outline.
When to pick this
New ClickHouse deployment from scratch and you want production patterns from day one.
MergeTree-variant matrix — when each one fits
Rough decision shape before a real engagement. Actual recommendation depends on your workload.
| Engine | Fits when | Avoid when |
|---|---|---|
| ReplicatedMergeTree | Append-only events, log analytics, immutable historical data — the production default. | You need upserts — pick ReplacingMergeTree or CollapsingMergeTree. |
| ReplacingMergeTree | Idempotent upserts where eventual dedup is acceptable; final-modifier SELECT pays the cost. | Need strong real-time dedup — final SELECT cost grows with table size. |
| CollapsingMergeTree | Fact-table updates with explicit sign columns; your pipeline can emit corrections. | Source can't produce sign rows — ReplacingMergeTree is simpler. |
| SummingMergeTree | Pre-aggregated counters where rows merge by sum; saves both storage and query cost. | Need raw rows back — aggregation is destructive. |
| AggregatingMergeTree | Stateful aggregations (uniqState, quantilesState) feeding materialized views. | Simple sums — SummingMergeTree is lighter. |