Fauna to Spotfire Integration

How Datrise loads Fauna into Spotfire

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

Sync is incremental: Datrise uses incremental refresh of the connected tables or in-memory data, so re-runs update only what changed. Date-partitioned facts. Spotfire can load data in-memory, so Datrise keeps the backing tables incremental so analyses refresh without full reloads.

Ideal for interactive analytical visualization and data science.

Endpoints

Fauna: Distributed document-relational database.

Spotfire: Visual analytics platform for interactive dashboards and data science workflows.

How Fauna entities map to Spotfire

Fauna entity	Spotfire object	Notes
collections	`fauna_collections`	id PK · custom fields → flattened columns for visualizations
documents	`fauna_documents`	id PK · linked to fauna_collections
indexes	`fauna_indexes`	id PK · linked to fauna_collections
functions	`fauna_functions`	id PK · linked to fauna_collections

FAQ

How does Datrise handle Fauna's custom fields in Spotfire?

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

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

It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.

Related pipelines

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