DatriseAI-first ETL

GitHub Webhook to CSV Files Integration

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

How Datrise loads GitHub Webhook into CSV Files

Datrise syncs GitHub Webhook's push events, pull requests, issues, releases, commits, and workflow runs 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

GitHub Webhook: Repository event stream delivered by webhook.

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

How GitHub Webhook entities map to CSV Files

GitHub Webhook entityCSV Files objectNotes
push eventsgithub_webhook_push_eventsISO-8601 timestamp columns events
pull requestsgithub_webhook_pull_requestsid PK · linked to github_webhook_push_events
issuesgithub_webhook_issuesid PK · linked to github_webhook_push_events
releasesgithub_webhook_releasesid PK · linked to github_webhook_push_events

FAQ

How does Datrise handle GitHub Webhook'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 GitHub Webhook 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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