DatriseAI-first ETL

Fauna to Amazon QuickSight Integration

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

How Datrise loads Fauna into Amazon QuickSight

Datrise syncs Fauna's collections, documents, indexes, functions, database schemas, and document history into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

Fauna: Distributed document-relational database.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Fauna entities map to Amazon QuickSight

Fauna entityAmazon QuickSight objectNotes
collectionsfauna_collectionsid PK · custom fields → flattened columns for analyses
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 Amazon QuickSight?

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

How does the Fauna to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

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