DatriseAI-first ETL

GitHub Microsoft SQL Server

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

How Datrise loads GitHub into Microsoft SQL Server

Datrise syncs GitHub's repositories, issues, pull requests, commits, and workflow runs 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

GitHub: Developer platform for repos, issues, and delivery workflows.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How GitHub entities map to Microsoft SQL Server

GitHub entityMicrosoft SQL Server objectNotes
repositoriesgithub_repositoriesid PK · custom fields → NVARCHAR(MAX) JSON columns
issuesgithub_issuesid PK · linked to github_repositories
pull requestsgithub_pull_requestsid PK · linked to github_repositories
commitsgithub_commitsid PK · linked to github_repositories

FAQ

How does Datrise handle GitHub'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 GitHub 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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