DatriseAI-first ETL

Docker Hub to Microsoft SQL Server Integration

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

How Datrise loads Docker Hub into Microsoft SQL Server

Datrise syncs Docker Hub's repositories, images, tags, pull counts, image manifests, and organizations into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

Docker Hub: Container image registry and distribution.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Docker Hub entities map to Microsoft SQL Server

Docker Hub entityMicrosoft SQL Server objectNotes
repositoriesdockerhub_repositoriesid PK · custom fields → NVARCHAR(MAX) JSON columns
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 Microsoft SQL Server?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.

How does the Docker Hub to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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