DatriseAI-first ETL

Fauna to Birst Integration

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

How Datrise loads Fauna into Birst

Datrise syncs Fauna's collections, documents, indexes, functions, database schemas, and document history into Birst as warehouse tables for Birst's automated star schema. 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 source tables Birst ingests, so re-runs update only what changed. Date-partitioned facts. Birst builds its own semantic layer, so Datrise lands conformed, well-keyed tables it can automate against.

Ideal for networked, governed enterprise BI.

Endpoints

Fauna: Distributed document-relational database.

Birst: Cloud BI with networked analytics and enterprise semantic layers.

How Fauna entities map to Birst

Fauna entityBirst 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 Birst?

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 Birst types.

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

It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.

Related pipelines

Early access

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