DatriseAI-first ETL

Aws Cloudtrail PostgreSQL

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

How Datrise loads Aws Cloudtrail into PostgreSQL

Datrise syncs Aws Cloudtrail's records, events, and configuration objects into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

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

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Aws Cloudtrail entities map to PostgreSQL

Aws Cloudtrail entityPostgreSQL objectNotes
recordsaws_cloudtrail_recordsid PK · custom fields → jsonb columns
eventsaws_cloudtrail_eventstimestamptz events
configuration objectsaws_cloudtrail_configuration_objectsid PK · linked to aws_cloudtrail_records

FAQ

How does Datrise handle Aws Cloudtrail's custom fields in PostgreSQL?

Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native PostgreSQL types.

How does the Aws Cloudtrail to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

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