DatriseAI-first ETL

Onfleet to Amazon Redshift Integration

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

How Datrise loads Onfleet into Amazon Redshift

Datrise syncs Onfleet's tasks, workers, teams, destinations, delivery events, and recipients 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

Onfleet: Last-mile delivery dispatch and driver tracking.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Onfleet entities map to Amazon Redshift

Onfleet entityAmazon Redshift objectNotes
tasksonfleet_tasksid PK · custom fields → SUPER columns
workersonfleet_workersid PK · linked to onfleet_tasks
teamsonfleet_teamsid PK · linked to onfleet_tasks
destinationsonfleet_destinationsid PK · linked to onfleet_tasks

FAQ

How does Datrise handle Onfleet'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 Onfleet 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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