DatriseAI-first ETL

Vincere to Amazon Redshift Integration

AI-first ETL from Vincere into Amazon Redshift. Governed entities, incremental sync, typed landing tables.

How Datrise loads Vincere into Amazon Redshift

Datrise syncs Vincere's candidates, jobs, contacts, companies, placements, and activity timelines 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

Vincere: Recruitment operating system for agency delivery teams.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Vincere entities map to Amazon Redshift

Vincere entityAmazon Redshift objectNotes
candidatesvincere_candidatesid PK · custom fields → SUPER columns
jobsvincere_jobsid PK · linked to vincere_candidates
contactsvincere_contactsid PK · linked to vincere_candidates
companiesvincere_companiesid PK · linked to vincere_candidates

FAQ

How does Datrise handle Vincere'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 Vincere 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.

Related pipelines

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