Mautic → PlanetScale
AI-first ETL from Mautic into PlanetScale. Governed entities, incremental sync, typed landing tables.
How Datrise loads Mautic into PlanetScale
Datrise syncs Mautic's contacts, accounts, deals, activities, and lifecycle events 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
Mautic: Open-source CRM for customizable sales and customer workflows.
PlanetScale: Serverless MySQL platform with safe schema workflows.
How Mautic entities map to PlanetScale
| Mautic entity | PlanetScale object | Notes |
|---|---|---|
| contacts | mautic_contacts | id PK · custom fields → JSON columns |
| accounts | mautic_accounts | id PK · linked to mautic_contacts |
| deals | mautic_deals | id PK · linked to mautic_contacts |
| activities | mautic_activities | DATETIME events |
FAQ
How does Datrise handle Mautic'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 Mautic 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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Early access
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