DatriseAI-first ETL

Fauna to ThoughtSpot Integration

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

How Datrise loads Fauna into ThoughtSpot

Datrise syncs Fauna's collections, documents, indexes, functions, database schemas, and document 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

Fauna: Distributed document-relational database.

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

How Fauna entities map to ThoughtSpot

Fauna entityThoughtSpot objectNotes
collectionsfauna_collectionsid PK · custom fields → flattened columns for searchable fields
documentsfauna_documentsid PK · linked to fauna_collections
indexesfauna_indexesid PK · linked to fauna_collections
functionsfauna_functionsid PK · linked to fauna_collections

FAQ

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

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

Related pipelines

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