Vitally to Neon Integration
AI-first ETL from Vitally into Neon. Governed entities, incremental sync, typed landing tables.
How Datrise loads Vitally into Neon
Datrise syncs Vitally's accounts, users, health scores, tasks, playbooks, and product usage 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
Vitally: Customer success health and account analytics.
Neon: Serverless Postgres destination with branching and autoscaling.
How Vitally entities map to Neon
| Vitally entity | Neon object | Notes |
|---|---|---|
| accounts | vitally_accounts | id PK · custom fields → jsonb columns |
| users | vitally_users | id PK · linked to vitally_accounts |
| health scores | vitally_health_scores | id PK · linked to vitally_accounts |
| tasks | vitally_tasks | id PK · linked to vitally_accounts |
FAQ
How does Datrise handle Vitally'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 Vitally 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
More destinations for Vitally
Early access
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