DatriseAI-first ETL

Amazon RDS to PlanetScale Integration

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 tables, rows, schemas, indexes, primary keys, and change streams 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: Managed relational database service on AWS.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Amazon RDS entities map to PlanetScale

Amazon RDS entityPlanetScale objectNotes
tablesamazon_rds_tablesid PK · custom fields → JSON columns
rowsamazon_rds_rowsid PK · linked to amazon_rds_tables
schemasamazon_rds_schemasid PK · linked to amazon_rds_tables
indexesamazon_rds_indexesid PK · linked to amazon_rds_tables

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.

Related pipelines

Early access

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