Datadog to PostgreSQL Integration

How Datrise loads Datadog into PostgreSQL

Datrise syncs Datadog's metrics, monitors, events, logs, dashboards, and incidents into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Datadog: Infrastructure monitoring, logs, and alerting.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Datadog entities map to PostgreSQL

Datadog entity	PostgreSQL object	Notes
metrics	`datadog_metrics`	id PK · custom fields → jsonb columns
monitors	`datadog_monitors`	id PK · linked to datadog_metrics
events	`datadog_events`	timestamptz events
logs	`datadog_logs`	id PK · linked to datadog_metrics

FAQ

How does Datrise handle Datadog's custom fields in PostgreSQL?

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

How does the Datadog to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

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