DatriseAI-first ETL

Intruder to ClickHouse Integration

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

How Datrise loads Intruder into ClickHouse

Datrise syncs Intruder's scans, issues, targets, severities, occurrences, and remediation statuses into ClickHouse as a MergeTree table per source entity. Flexible or custom fields land in JSON or Map columns, and timestamps such as created, updated, and status changes are typed as DateTime64.

Sync is incremental: Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge, so re-runs update only what changed. Partition by month and order by (entity id, updated-at) for fast range scans. ClickHouse deduplicates asynchronously on merge, so Datrise uses ReplacingMergeTree and FINAL-safe queries rather than assuming immediate upserts.

Ideal for high-volume event analytics that need sub-second aggregation.

Endpoints

Intruder: Continuous vulnerability scanning for internet assets.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Intruder entities map to ClickHouse

Intruder entityClickHouse objectNotes
scansintruder_scansid PK · custom fields → JSON or Map 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 ClickHouse?

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

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

It runs incrementally — Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge.

Related pipelines

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