DatriseAI-first ETL

Onfleet ThoughtSpot

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

How Datrise loads Onfleet into ThoughtSpot

Datrise syncs Onfleet's records, events, and configuration objects into ThoughtSpot as warehouse tables ThoughtSpot indexes for search. Flexible or custom fields land in flattened columns for searchable fields, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the indexed tables, so re-runs update only what changed. Date-partitioned facts for live-query performance. ThoughtSpot search relies on clear names and relationships, so Datrise lands well-named, joinable tables.

Ideal for natural-language search analytics over a warehouse.

Endpoints

Onfleet: SaaS or API data source for analytics and warehouse sync.

ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.

How Onfleet entities map to ThoughtSpot

Onfleet entityThoughtSpot objectNotes
recordsonfleet_recordsid PK · custom fields → flattened columns for searchable fields
eventsonfleet_eventsdate/time columns events
configuration objectsonfleet_configuration_objectsid PK · linked to onfleet_records

FAQ

How does Datrise handle Onfleet's custom fields in ThoughtSpot?

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

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

It runs incrementally — Datrise uses incremental refresh of the indexed tables.

Related pipelines

Early access

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