Reply Io → PlanetScale
AI-first ETL from Reply Io into PlanetScale. Governed entities, incremental sync, typed landing tables.
How Datrise loads Reply Io into PlanetScale
Datrise syncs Reply Io's records, events, and configuration objects 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
Reply Io: SaaS or API data source for analytics and warehouse sync.
PlanetScale: Serverless MySQL platform with safe schema workflows.
How Reply Io entities map to PlanetScale
| Reply Io entity | PlanetScale object | Notes |
|---|---|---|
| records | reply_io_records | id PK · custom fields → JSON columns |
| events | reply_io_events | DATETIME events |
| configuration objects | reply_io_configuration_objects | id PK · linked to reply_io_records |
FAQ
How does Datrise handle Reply 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 Reply 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 Reply Io
More sources for PlanetScale
Early access
Connect Reply Io to PlanetScale the easy way
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