Day.ai to PlanetScale Integration
AI-first ETL from Day.ai into PlanetScale. Governed entities, incremental sync, typed landing tables.
How Datrise loads Day.ai into PlanetScale
Datrise syncs Day.ai's contacts, companies, meetings, opportunities, AI summaries, and relationship signals into PlanetScale as a typed table per source entity. Flexible or custom fields land in JSON columns, and timestamps such as created, updated, and status changes are typed as DATETIME.
Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE, so re-runs update only what changed. Vitess sharding by tenant or entity key for very large tables. PlanetScale disallows foreign-key constraints by default, so Datrise models relationships by stable id columns rather than enforced FKs.
Ideal for horizontally scalable MySQL apps on Vitess.
Endpoints
Day.ai: CRM that builds records from meetings and email automatically.
PlanetScale: Serverless MySQL platform with safe schema workflows.
How Day.ai entities map to PlanetScale
| Day.ai entity | PlanetScale object | Notes |
|---|---|---|
| contacts | day_ai_contacts | id PK · custom fields → JSON columns |
| companies | day_ai_companies | id PK · linked to day_ai_contacts |
| meetings | day_ai_meetings | id PK · linked to day_ai_contacts |
| opportunities | day_ai_opportunities | id PK · linked to day_ai_contacts |
FAQ
How does Datrise handle Day.ai's custom fields in PlanetScale?
Flexible values are stored as JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native PlanetScale types.
How does the Day.ai to PlanetScale sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE.
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