DatriseAI-first ETL

Sellsy to Apache Superset Integration

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

How Datrise loads Sellsy into Apache Superset

Datrise syncs Sellsy's prospects, opportunities, estimates, invoices, tickets, and timeline events 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

Sellsy: French CRM with quoting, invoicing, and support tickets.

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

How Sellsy entities map to Apache Superset

Sellsy entityApache Superset objectNotes
prospectssellsy_prospectsid PK · custom fields → flattened columns for the explore UI
opportunitiessellsy_opportunitiesid PK · linked to sellsy_prospects
estimatessellsy_estimatesid PK · linked to sellsy_prospects
invoicessellsy_invoicesid PK · linked to sellsy_prospects

FAQ

How does Datrise handle Sellsy'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 Sellsy 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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