DatriseAI-first ETL

Onfleet to Spotfire Integration

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

How Datrise loads Onfleet into Spotfire

Datrise syncs Onfleet's tasks, workers, teams, destinations, delivery events, and recipients into Spotfire as warehouse tables or in-memory data for Spotfire analyses. Flexible or custom fields land in flattened columns for visualizations, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables or in-memory data, so re-runs update only what changed. Date-partitioned facts. Spotfire can load data in-memory, so Datrise keeps the backing tables incremental so analyses refresh without full reloads.

Ideal for interactive analytical visualization and data science.

Endpoints

Onfleet: Last-mile delivery dispatch and driver tracking.

Spotfire: Visual analytics platform for interactive dashboards and data science workflows.

How Onfleet entities map to Spotfire

Onfleet entitySpotfire objectNotes
tasksonfleet_tasksid PK · custom fields → flattened columns for visualizations
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 Spotfire?

Flexible values are stored as flattened columns for visualizations, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Spotfire types.

How does the Onfleet to Spotfire sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.

Related pipelines

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