DatriseAI-first ETL

Confluence to Microsoft SQL Server Integration

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

How Datrise loads Confluence into Microsoft SQL Server

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

Confluence: Team wiki and documentation workspace.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Confluence entities map to Microsoft SQL Server

Confluence entityMicrosoft SQL Server objectNotes
spacesconfluence_spacesid PK · custom fields → NVARCHAR(MAX) JSON columns
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 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 Confluence 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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