DatriseAI-first ETL

Docker Hub to Spotfire Integration

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

How Datrise loads Docker Hub into Spotfire

Datrise syncs Docker Hub's repositories, images, tags, pull counts, image manifests, and organizations 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

Docker Hub: Container image registry and distribution.

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

How Docker Hub entities map to Spotfire

Docker Hub entitySpotfire objectNotes
repositoriesdockerhub_repositoriesid PK · custom fields → flattened columns for visualizations
imagesdockerhub_imagesid PK · linked to dockerhub_repositories
tagsdockerhub_tagsid PK · linked to dockerhub_repositories
pull countsdockerhub_pull_countsid PK · linked to dockerhub_repositories

FAQ

How does Datrise handle Docker Hub'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 Docker Hub 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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