VictorOps to DuckDB Integration

How Datrise loads VictorOps into DuckDB

Datrise syncs VictorOps's incidents, alerts, on-call schedules, teams, escalation policies, and acknowledgements into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

VictorOps: On-call rotation and incident alerting.

DuckDB: In-process analytics database for fast local OLAP.

How VictorOps entities map to DuckDB

VictorOps entity	DuckDB object	Notes
incidents	`victorops_incidents`	id PK · custom fields → JSON or STRUCT columns
alerts	`victorops_alerts`	id PK · linked to victorops_incidents
on-call schedules	`victorops_on_call_schedules`	id PK · linked to victorops_incidents
teams	`victorops_teams`	id PK · linked to victorops_incidents

FAQ

How does Datrise handle VictorOps's custom fields in DuckDB?

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

How does the VictorOps to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

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