DatriseAI-first ETL

Datadog to Oracle Database Integration

AI-first ETL from Datadog into Oracle Database. Governed entities, incremental sync, typed landing tables.

How Datrise loads Datadog into Oracle Database

Datrise syncs Datadog's metrics, monitors, events, logs, dashboards, and incidents into Oracle Database as a typed table per source entity. Flexible or custom fields land in JSON or CLOB columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses a watermark on updated-at, applied with MERGE INTO, so re-runs update only what changed. Optional range partitioning by load date. Oracle treats an empty string as NULL, so Datrise distinguishes blank source values from missing ones during load.

Ideal for enterprise data teams consolidating CRM data into an Oracle warehouse.

Endpoints

Datadog: Infrastructure monitoring, logs, and alerting.

Oracle Database: Enterprise RDBMS with advanced partitioning and HA.

How Datadog entities map to Oracle Database

Datadog entityOracle Database objectNotes
metricsdatadog_metricsid PK · custom fields → JSON or CLOB columns
monitorsdatadog_monitorsid PK · linked to datadog_metrics
eventsdatadog_eventsTIMESTAMP WITH TIME ZONE events
logsdatadog_logsid PK · linked to datadog_metrics

FAQ

How does Datrise handle Datadog's custom fields in Oracle Database?

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

How does the Datadog to Oracle Database sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with MERGE INTO.

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