DatriseAI-first ETL

Zenefits to Amazon Redshift Integration

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

How Datrise loads Zenefits into Amazon Redshift

Datrise syncs Zenefits's employees, departments, employments, time off requests, benefits enrollments, and compensation records 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

Zenefits: HR, benefits, and payroll administration.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Zenefits entities map to Amazon Redshift

Zenefits entityAmazon Redshift objectNotes
employeeszenefits_employeesid PK · custom fields → SUPER columns
departmentszenefits_departmentsid PK · linked to zenefits_employees
employmentszenefits_employmentsid PK · linked to zenefits_employees
time off requestszenefits_time_off_requestsid PK · linked to zenefits_employees

FAQ

How does Datrise handle Zenefits'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 Zenefits 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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