DatriseAI-first ETL

Intruder to Snowflake Integration

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

How Datrise loads Intruder into Snowflake

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

Sync is incremental: Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size, so re-runs update only what changed. Automatic micro-partitioning, with optional clustering keys on high-cardinality ids. Snowflake upper-cases unquoted identifiers, so Datrise standardizes on lower-case quoted names to keep column references stable.

Ideal for central analytics warehouses feeding BI and AI workloads.

Endpoints

Intruder: Continuous vulnerability scanning for internet assets.

Snowflake: Cloud data warehouse with separated compute and storage.

How Intruder entities map to Snowflake

Intruder entitySnowflake objectNotes
scansintruder_scansid PK · custom fields → VARIANT 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 Snowflake?

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

How does the Intruder to Snowflake sync stay up to date?

It runs incrementally — Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size.

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