Greenhouse to ThoughtSpot Integration
AI-first ETL from Greenhouse into ThoughtSpot. Governed entities, incremental sync, typed landing tables.
How Datrise loads Greenhouse into ThoughtSpot
Datrise syncs Greenhouse's candidates, applications, jobs, interviews, scorecards, and offers into ThoughtSpot as warehouse tables ThoughtSpot indexes for search. Flexible or custom fields land in flattened columns for searchable fields, and timestamps such as created, updated, and status changes are typed as date/time columns.
Sync is incremental: Datrise uses incremental refresh of the indexed tables, so re-runs update only what changed. Date-partitioned facts for live-query performance. ThoughtSpot search relies on clear names and relationships, so Datrise lands well-named, joinable tables.
Ideal for natural-language search analytics over a warehouse.
Endpoints
Greenhouse: Applicant tracking and structured hiring.
ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.
How Greenhouse entities map to ThoughtSpot
| Greenhouse entity | ThoughtSpot object | Notes |
|---|---|---|
| candidates | greenhouse_candidates | id PK · custom fields → flattened columns for searchable fields |
| applications | greenhouse_applications | id PK · linked to greenhouse_candidates |
| jobs | greenhouse_jobs | id PK · linked to greenhouse_candidates |
| interviews | greenhouse_interviews | id PK · linked to greenhouse_candidates |
FAQ
How does Datrise handle Greenhouse's custom fields in ThoughtSpot?
Flexible values are stored as flattened columns for searchable fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native ThoughtSpot types.
How does the Greenhouse to ThoughtSpot sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the indexed tables.
Related pipelines
More destinations for Greenhouse
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