DatriseAI-first ETL

Lever to ClickHouse Integration

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

How Datrise loads Lever into ClickHouse

Datrise syncs Lever's candidates, opportunities, postings, interviews, offers, and feedback forms 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

Lever: Applicant tracking and candidate relationship management.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Lever entities map to ClickHouse

Lever entityClickHouse objectNotes
candidateslever_candidatesid PK · custom fields → JSON or Map columns
opportunitieslever_opportunitiesid PK · linked to lever_candidates
postingslever_postingsid PK · linked to lever_candidates
interviewslever_interviewsid PK · linked to lever_candidates

FAQ

How does Datrise handle Lever'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 Lever 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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