DatriseAI-first ETL

Confluence to Spotfire Integration

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

How Datrise loads Confluence into Spotfire

Datrise syncs Confluence's spaces, pages, blog posts, comments, attachments, and page versions 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

Confluence: Team wiki and documentation workspace.

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

How Confluence entities map to Spotfire

Confluence entitySpotfire objectNotes
spacesconfluence_spacesid PK · custom fields → flattened columns for visualizations
pagesconfluence_pagesid PK · linked to confluence_spaces
blog postsconfluence_blog_postsid PK · linked to confluence_spaces
commentsconfluence_commentsid PK · linked to confluence_spaces

FAQ

How does Datrise handle Confluence'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 Confluence to Spotfire sync stay up to date?

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

Related pipelines

Early access

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