Amazon Rds → PlanetScale
AI-first ETL from Amazon Rds into PlanetScale. Governed entities, incremental sync, typed landing tables.
How Datrise loads Amazon Rds into PlanetScale
Datrise syncs Amazon Rds'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
Amazon Rds: SaaS or API data source for analytics and warehouse sync.
PlanetScale: Serverless MySQL platform with safe schema workflows.
How Amazon Rds entities map to PlanetScale
| Amazon Rds entity | PlanetScale object | Notes |
|---|---|---|
| records | amazon_rds_records | id PK · custom fields → JSON columns |
| events | amazon_rds_events | DATETIME events |
| configuration objects | amazon_rds_configuration_objects | id PK · linked to amazon_rds_records |
FAQ
How does Datrise handle Amazon Rds'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 Amazon Rds 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 Amazon Rds 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.