DatriseAI-first ETL

Public API to Spotfire Integration

AI-first ETL from Public API into Spotfire. Governed entities, incremental sync, typed landing tables.

How Datrise loads Public API into Spotfire

Datrise syncs Public API's records, response payloads, pagination cursors, request parameters, schemas, and fetch timestamps 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

Public API: Generic REST endpoint pulled on a schedule.

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

How Public API entities map to Spotfire

Public API entitySpotfire objectNotes
recordspublic_api_recordsid PK · custom fields → flattened columns for visualizations
response payloadspublic_api_response_payloadsid PK · linked to public_api_records
pagination cursorspublic_api_pagination_cursorsid PK · linked to public_api_records
request parameterspublic_api_request_parametersid PK · linked to public_api_records

FAQ

How does Datrise handle Public API'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 Public API 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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