DatriseAI-first ETL

Workday Amazon Redshift

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

How Datrise loads Workday into Amazon Redshift

Datrise syncs Workday's HR, finance entities, organizational structures, and operational 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

Workday: Enterprise HR and finance source for operational reporting.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Workday entities map to Amazon Redshift

Workday entityAmazon Redshift objectNotes
HRworkday_hrid PK · custom fields → SUPER columns
finance entitiesworkday_finance_entitiesid PK · linked to workday_hr
organizational structuresworkday_organizational_structuresid PK · linked to workday_hr
operational eventsworkday_operational_eventsTIMESTAMPTZ events

FAQ

How does Datrise handle Workday'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 Workday 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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