DatriseAI-first ETL

Whisky Hunter Neon

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

How Datrise loads Whisky Hunter into Neon

Datrise syncs Whisky Hunter'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

Whisky Hunter: SaaS or API data source for analytics and warehouse sync.

Neon: Serverless Postgres destination with branching and autoscaling.

How Whisky Hunter entities map to Neon

Whisky Hunter entityNeon objectNotes
recordswhisky_hunter_recordsid PK · custom fields → jsonb columns
eventswhisky_hunter_eventstimestamptz events
configuration objectswhisky_hunter_configuration_objectsid PK · linked to whisky_hunter_records

FAQ

How does Datrise handle Whisky Hunter'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 Whisky Hunter 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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