DatriseAI-first ETL

Instatus to ThoughtSpot Integration

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

How Datrise loads Instatus into ThoughtSpot

Datrise syncs Instatus's incidents, components, incident updates, subscribers, status page views, and uptime history 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

Instatus: Fast status pages with incident timelines and subscribers.

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

How Instatus entities map to ThoughtSpot

Instatus entityThoughtSpot objectNotes
incidentsinstatus_incidentsid PK · custom fields → flattened columns for searchable fields
componentsinstatus_componentsid PK · linked to instatus_incidents
incident updatesinstatus_incident_updatesid PK · linked to instatus_incidents
subscribersinstatus_subscribersid PK · linked to instatus_incidents

FAQ

How does Datrise handle Instatus'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 Instatus to ThoughtSpot sync stay up to date?

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

Related pipelines

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