DatriseAI-first ETL

Manatal Amazon Redshift

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 contacts, accounts, deals, activities, and lifecycle events 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: Recruiting CRM/ATS for candidates, pipelines, and placements.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Manatal entities map to Amazon Redshift

Manatal entityAmazon Redshift objectNotes
contactsmanatal_contactsid PK · custom fields → SUPER columns
accountsmanatal_accountsid PK · linked to manatal_contacts
dealsmanatal_dealsid PK · linked to manatal_contacts
activitiesmanatal_activitiesTIMESTAMPTZ events

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.

Related pipelines

Early access

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