DatriseAI-first ETL

PipeRun ClickHouse

AI-first ETL from PipeRun into ClickHouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads PipeRun into ClickHouse

Datrise syncs PipeRun's contacts, accounts, deals, activities, and lifecycle events into ClickHouse as a MergeTree table per source entity. Flexible or custom fields land in JSON or Map columns, and timestamps such as created, updated, and status changes are typed as DateTime64.

Sync is incremental: Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge, so re-runs update only what changed. Partition by month and order by (entity id, updated-at) for fast range scans. ClickHouse deduplicates asynchronously on merge, so Datrise uses ReplacingMergeTree and FINAL-safe queries rather than assuming immediate upserts.

Ideal for high-volume event analytics that need sub-second aggregation.

Endpoints

PipeRun: CRM widely used in Latin America for sales pipeline and customer ops.

ClickHouse: Columnar OLAP engine for fast aggregations.

How PipeRun entities map to ClickHouse

PipeRun entityClickHouse objectNotes
contactspiperun_contactsid PK · custom fields → JSON or Map columns
accountspiperun_accountsid PK · linked to piperun_contacts
dealspiperun_dealsid PK · linked to piperun_contacts
activitiespiperun_activitiesDateTime64 events

FAQ

How does Datrise handle PipeRun's custom fields in ClickHouse?

Flexible values are stored as JSON or Map columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native ClickHouse types.

How does the PipeRun to ClickHouse sync stay up to date?

It runs incrementally — Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge.

Related pipelines

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