Manatal to Birst Integration
AI-first ETL from Manatal into Birst. Governed entities, incremental sync, typed landing tables.
How Datrise loads Manatal into Birst
Datrise syncs Manatal's candidates, jobs, applications, pipeline stages, match scores, and clients into Birst as warehouse tables for Birst's automated star schema. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the source tables Birst ingests, so re-runs update only what changed. Date-partitioned facts. Birst builds its own semantic layer, so Datrise lands conformed, well-keyed tables it can automate against.
Ideal for networked, governed enterprise BI.
Endpoints
Manatal: AI recruitment software with candidate scoring.
Birst: Cloud BI with networked analytics and enterprise semantic layers.
How Manatal entities map to Birst
| Manatal entity | Birst object | Notes |
|---|---|---|
| candidates | manatal_candidates | id PK · custom fields → flattened columns |
| jobs | manatal_jobs | id PK · linked to manatal_candidates |
| applications | manatal_applications | id PK · linked to manatal_candidates |
| pipeline stages | manatal_pipeline_stages | id PK · linked to manatal_candidates |
FAQ
How does Datrise handle Manatal's custom fields in Birst?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Birst types.
How does the Manatal to Birst sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.
Related pipelines
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