DatriseAI-first ETL

Github Webhook Neon

AI-first ETL from Github Webhook into Neon. Governed entities, incremental sync, typed landing tables.

How Datrise loads Github Webhook into Neon

Datrise syncs Github Webhook's records, events, and configuration objects into Neon as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative partitioning by load date. Neon separates compute from storage, so Datrise batches writes to keep autoscaling compute from cold-starting on every small change.

Ideal for serverless Postgres workloads that scale to zero between syncs.

Endpoints

Github Webhook: SaaS or API data source for analytics and warehouse sync.

Neon: Serverless Postgres destination with branching and autoscaling.

How Github Webhook entities map to Neon

Github Webhook entityNeon objectNotes
recordsgithub_webhook_recordsid PK · custom fields → jsonb columns
eventsgithub_webhook_eventstimestamptz events
configuration objectsgithub_webhook_configuration_objectsid PK · linked to github_webhook_records

FAQ

How does Datrise handle Github Webhook's custom fields in Neon?

Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Neon types.

How does the Github Webhook to Neon sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

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