DatriseAI-first ETL

Crelate ClickHouse

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

How Datrise loads Crelate into ClickHouse

Datrise syncs Crelate'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

Crelate: Recruiting CRM/ATS for candidates, pipelines, and placements.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Crelate entities map to ClickHouse

Crelate entityClickHouse objectNotes
contactscrelate_contactsid PK · custom fields → JSON or Map columns
accountscrelate_accountsid PK · linked to crelate_contacts
dealscrelate_dealsid PK · linked to crelate_contacts
activitiescrelate_activitiesDateTime64 events

FAQ

How does Datrise handle Crelate'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 Crelate 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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