Apollo → Spotfire
AI-first ETL from Apollo into Spotfire. Governed entities, incremental sync, typed landing tables.
How Datrise loads Apollo into Spotfire
Datrise syncs Apollo's sales intelligence records, account engagement, and outbound activity 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
Apollo: Sales intelligence and engagement platform with account-level activity.
Spotfire: Visual analytics platform for interactive dashboards and data science workflows.
How Apollo entities map to Spotfire
| Apollo entity | Spotfire object | Notes |
|---|---|---|
| sales intelligence records | apollo_sales_intelligence_records | id PK · custom fields → flattened columns for visualizations |
| account engagement | apollo_account_engagement | id PK · linked to apollo_sales_intelligence_records |
| outbound activity | apollo_outbound_activity | date/time columns events |
FAQ
How does Datrise handle Apollo'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 Apollo to Spotfire sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.
Related pipelines
More destinations for Apollo
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