DatriseAI-first ETL

Intruder to Amazon Redshift Integration

AI-first ETL from Intruder into Amazon Redshift. Governed entities, incremental sync, typed landing tables.

How Datrise loads Intruder into Amazon Redshift

Datrise syncs Intruder's scans, issues, targets, severities, occurrences, and remediation statuses into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.

Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.

Ideal for AWS-native warehouses already using the Redshift ecosystem.

Endpoints

Intruder: Continuous vulnerability scanning for internet assets.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Intruder entities map to Amazon Redshift

Intruder entityAmazon Redshift objectNotes
scansintruder_scansid PK · custom fields → SUPER columns
issuesintruder_issuesid PK · linked to intruder_scans
targetsintruder_targetsid PK · linked to intruder_scans
severitiesintruder_severitiesid PK · linked to intruder_scans

FAQ

How does Datrise handle Intruder's custom fields in Amazon Redshift?

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

How does the Intruder to Amazon Redshift sync stay up to date?

It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.

Related pipelines

Early access

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