DatriseAI-first ETL

Greenhouse to ClickHouse Integration

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

How Datrise loads Greenhouse into ClickHouse

Datrise syncs Greenhouse's candidates, applications, jobs, interviews, scorecards, and offers 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

Greenhouse: Applicant tracking and structured hiring.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Greenhouse entities map to ClickHouse

Greenhouse entityClickHouse objectNotes
candidatesgreenhouse_candidatesid PK · custom fields → JSON or Map columns
applicationsgreenhouse_applicationsid PK · linked to greenhouse_candidates
jobsgreenhouse_jobsid PK · linked to greenhouse_candidates
interviewsgreenhouse_interviewsid PK · linked to greenhouse_candidates

FAQ

How does Datrise handle Greenhouse'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 Greenhouse 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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