DatriseAI-first ETL

Docker Hub to CSV Files Integration

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

How Datrise loads Docker Hub into CSV Files

Datrise syncs Docker Hub's repositories, images, tags, pull counts, image manifests, and organizations into CSV Files as one CSV per source entity. Flexible or custom fields land in JSON-encoded strings for nested fields, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes a fresh, fully-typed CSV per entity each run, so re-runs update only what changed. Optional date-suffixed files for change tracking. CSV has no types, so Datrise emits a companion schema and quotes/escapes consistently so downstream loaders don't misparse commas and newlines.

Ideal for portable hand-off into any tool that ingests delimited files.

Endpoints

Docker Hub: Container image registry and distribution.

CSV Files: Flat-file destination for exports and lightweight data sharing.

How Docker Hub entities map to CSV Files

Docker Hub entityCSV Files objectNotes
repositoriesdockerhub_repositoriesid PK · custom fields → JSON-encoded strings for nested fields
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 CSV Files?

Flexible values are stored as JSON-encoded strings for nested fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native CSV Files types.

How does the Docker Hub to CSV Files sync stay up to date?

It runs incrementally — Datrise uses writes a fresh, fully-typed CSV per entity each run.

Related pipelines

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