Manatal to Amazon Redshift Integration
AI-first ETL from Manatal into Amazon Redshift. Governed entities, incremental sync, typed landing tables.
How Datrise loads Manatal into Amazon Redshift
Datrise syncs Manatal's candidates, jobs, applications, pipeline stages, match scores, and clients into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.
Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.
Ideal for AWS-native warehouses already using the Redshift ecosystem.
Endpoints
Manatal: AI recruitment software with candidate scoring.
Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.
How Manatal entities map to Amazon Redshift
| Manatal entity | Amazon Redshift object | Notes |
|---|---|---|
| candidates | manatal_candidates | id PK · custom fields → SUPER 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 Amazon Redshift?
Flexible values are stored as SUPER columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Redshift types.
How does the Manatal to Amazon Redshift sync stay up to date?
It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.
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Early access
Connect Manatal to Amazon Redshift the easy way
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