Customer.io → PlanetScale
AI-first ETL from Customer.io into PlanetScale. Governed entities, incremental sync, typed landing tables.
How Datrise loads Customer.io into PlanetScale
Datrise syncs Customer.io's profiles, segments, campaigns, deliveries, and conversion 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
Customer.io: Messaging automation based on product and behavioral data.
PlanetScale: Serverless MySQL platform with safe schema workflows.
How Customer.io entities map to PlanetScale
| Customer.io entity | PlanetScale object | Notes |
|---|---|---|
| profiles | customer_io_profiles | id PK · custom fields → JSON columns |
| segments | customer_io_segments | id PK · linked to customer_io_profiles |
| campaigns | customer_io_campaigns | id PK · linked to customer_io_profiles |
| deliveries | customer_io_deliveries | id PK · linked to customer_io_profiles |
FAQ
How does Datrise handle Customer.io'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 Customer.io 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
More destinations for Customer.io
More sources for PlanetScale
Early access
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