GitHub Webhook to Microsoft SQL Server Integration
AI-first ETL from GitHub Webhook into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.
How Datrise loads GitHub Webhook into Microsoft SQL Server
Datrise syncs GitHub Webhook's push events, pull requests, issues, releases, 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 Webhook: Repository event stream delivered by webhook.
Microsoft SQL Server: Microsoft relational DB with enterprise features.
How GitHub Webhook entities map to Microsoft SQL Server
| GitHub Webhook entity | Microsoft SQL Server object | Notes |
|---|---|---|
| push events | github_webhook_push_events | datetime2 events |
| pull requests | github_webhook_pull_requests | id PK · linked to github_webhook_push_events |
| issues | github_webhook_issues | id PK · linked to github_webhook_push_events |
| releases | github_webhook_releases | id PK · linked to github_webhook_push_events |
FAQ
How does Datrise handle GitHub Webhook'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 Webhook 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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Early access
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