DatriseAI-first ETL

Microsoft Dataverse Apache Superset

AI-first ETL from Microsoft Dataverse into Apache Superset. Governed entities, incremental sync, typed landing tables.

How Datrise loads Microsoft Dataverse into Apache Superset

Datrise syncs Microsoft Dataverse's records, events, and configuration objects into Apache Superset as governed SQL tables Superset queries directly. Flexible or custom fields land in flattened columns for the explore UI, and timestamps such as created, updated, and status changes are typed as temporal columns for time-series charts.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned tables to keep dashboards responsive. Superset charts run live SQL, so Datrise lands query-friendly, indexed tables rather than wide raw payloads.

Ideal for open-source dashboards over your own database.

Endpoints

Microsoft Dataverse: SaaS or API data source for analytics and warehouse sync.

Apache Superset: Open-source BI for SQL exploration, charts, and dashboard publishing.

How Microsoft Dataverse entities map to Apache Superset

Microsoft Dataverse entityApache Superset objectNotes
recordsmicrosoft_dataverse_recordsid PK · custom fields → flattened columns for the explore UI
eventsmicrosoft_dataverse_eventstemporal columns for time-series charts events
configuration objectsmicrosoft_dataverse_configuration_objectsid PK · linked to microsoft_dataverse_records

FAQ

How does Datrise handle Microsoft Dataverse's custom fields in Apache Superset?

Flexible values are stored as flattened columns for the explore UI, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Apache Superset types.

How does the Microsoft Dataverse to Apache Superset sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

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