Datadog to GoodData Integration
AI-first ETL from Datadog into GoodData. Governed entities, incremental sync, typed landing tables.
How Datrise loads Datadog into GoodData
Datrise syncs Datadog's metrics, monitors, events, logs, dashboards, and incidents into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.
Ideal for embedded, multi-tenant analytics.
Endpoints
Datadog: Infrastructure monitoring, logs, and alerting.
GoodData: Composable analytics platform with headless BI and embedded dashboards.
How Datadog entities map to GoodData
| Datadog entity | GoodData object | Notes |
|---|---|---|
| metrics | datadog_metrics | id PK · custom fields → flattened columns |
| monitors | datadog_monitors | id PK · linked to datadog_metrics |
| events | datadog_events | date dimensions events |
| logs | datadog_logs | id PK · linked to datadog_metrics |
FAQ
How does Datrise handle Datadog's custom fields in GoodData?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native GoodData types.
How does the Datadog to GoodData sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Datadog
Early access
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