DatriseAI-first ETL

Aws Cloudtrail PlanetScale

AI-first ETL from Aws Cloudtrail into PlanetScale. Governed entities, incremental sync, typed landing tables.

How Datrise loads Aws Cloudtrail into PlanetScale

Datrise syncs Aws Cloudtrail'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

Aws Cloudtrail: SaaS or API data source for analytics and warehouse sync.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Aws Cloudtrail entities map to PlanetScale

Aws Cloudtrail entityPlanetScale objectNotes
recordsaws_cloudtrail_recordsid PK · custom fields → JSON columns
eventsaws_cloudtrail_eventsDATETIME events
configuration objectsaws_cloudtrail_configuration_objectsid PK · linked to aws_cloudtrail_records

FAQ

How does Datrise handle Aws Cloudtrail'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 Aws Cloudtrail 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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