Day.ai → Neon
AI-first ETL from Day.ai into Neon. Governed entities, incremental sync, typed landing tables.
How Datrise loads Day.ai into Neon
Datrise syncs Day.ai's contacts, accounts, deals, activities, and lifecycle events 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
Day.ai: AI-native CRM for relationship data, enrichment, and workflow automation.
Neon: Serverless Postgres destination with branching and autoscaling.
How Day.ai entities map to Neon
| Day.ai entity | Neon object | Notes |
|---|---|---|
| contacts | day_ai_contacts | id PK · custom fields → jsonb columns |
| accounts | day_ai_accounts | id PK · linked to day_ai_contacts |
| deals | day_ai_deals | id PK · linked to day_ai_contacts |
| activities | day_ai_activities | timestamptz events |
FAQ
How does Datrise handle Day.ai'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 Day.ai to Neon sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE.
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Early access
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