DatriseAI-first ETL

Fauna to Yellowfin Integration

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

How Datrise loads Fauna into Yellowfin

Datrise syncs Fauna's collections, documents, indexes, functions, database schemas, and document history into Yellowfin as warehouse tables Yellowfin builds views on. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. Yellowfin views reference columns by name, so Datrise lands stable, well-typed columns to keep reports valid.

Ideal for dashboards with automated data storytelling.

Endpoints

Fauna: Distributed document-relational database.

Yellowfin: BI suite with dashboards, automated insights, and data storytelling.

How Fauna entities map to Yellowfin

Fauna entityYellowfin objectNotes
collectionsfauna_collectionsid PK · custom fields → flattened columns
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 Yellowfin?

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

How does the Fauna to Yellowfin sync stay up to date?

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

Related pipelines

Early access

Connect Fauna to Yellowfin the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.