DatriseAI-first ETL

Pagerduty to ClickHouse Integration

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

How Datrise loads Pagerduty into ClickHouse

Datrise syncs Pagerduty's incidents, services, schedules, escalation policies, log entries, and responders 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

Pagerduty: Incident response, on-call schedules, and escalation.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Pagerduty entities map to ClickHouse

Pagerduty entityClickHouse objectNotes
incidentspagerduty_incidentsid PK · custom fields → JSON or Map columns
servicespagerduty_servicesid PK · linked to pagerduty_incidents
schedulespagerduty_schedulesid PK · linked to pagerduty_incidents
escalation policiespagerduty_escalation_policiesid PK · linked to pagerduty_incidents

FAQ

How does Datrise handle Pagerduty'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 Pagerduty 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.

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