Delighted → PlanetScale
AI-first ETL from Delighted into PlanetScale. Governed entities, incremental sync, typed landing tables.
How Datrise loads Delighted into PlanetScale
Datrise syncs Delighted's surveys, responses, scores, and follow-up workflows 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
Delighted: NPS and micro-survey feedback platform.
PlanetScale: Serverless MySQL platform with safe schema workflows.
How Delighted entities map to PlanetScale
| Delighted entity | PlanetScale object | Notes |
|---|---|---|
| surveys | delighted_surveys | id PK · custom fields → JSON columns |
| responses | delighted_responses | id PK · linked to delighted_surveys |
| scores | delighted_scores | id PK · linked to delighted_surveys |
| follow-up workflows | delighted_follow_up_workflows | id PK · linked to delighted_surveys |
FAQ
How does Datrise handle Delighted'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 Delighted to PlanetScale sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE.
Related pipelines
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Early access
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