Particle to PlanetScale Integration
AI-first ETL from Particle into PlanetScale. Governed entities, incremental sync, typed landing tables.
How Datrise loads Particle into PlanetScale
Datrise syncs Particle's devices, events, variables, firmware versions, product fleets, and device logs 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
Particle: IoT device fleet telemetry and events.
PlanetScale: Serverless MySQL platform with safe schema workflows.
How Particle entities map to PlanetScale
| Particle entity | PlanetScale object | Notes |
|---|---|---|
| devices | particle_devices | id PK · custom fields → JSON columns |
| events | particle_events | DATETIME events |
| variables | particle_variables | id PK · linked to particle_devices |
| firmware versions | particle_firmware_versions | id PK · linked to particle_devices |
FAQ
How does Datrise handle Particle'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 Particle 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
Connect Particle to PlanetScale the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.