DatriseAI-first ETL

Heroku to ThoughtSpot Integration

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

How Datrise loads Heroku into ThoughtSpot

Datrise syncs Heroku's apps, dynos, releases, add-ons, config vars, and build logs 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

Heroku: Application platform with dynos and add-ons.

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

How Heroku entities map to ThoughtSpot

Heroku entityThoughtSpot objectNotes
appsheroku_appsid PK · custom fields → flattened columns for searchable fields
dynosheroku_dynosid PK · linked to heroku_apps
releasesheroku_releasesid PK · linked to heroku_apps
add-onsheroku_add_onsid PK · linked to heroku_apps

FAQ

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

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

Related pipelines

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