DatriseAI-first ETL

Sellsy to Redash Integration

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

How Datrise loads Sellsy into Redash

Datrise syncs Sellsy's prospects, opportunities, estimates, invoices, tickets, and timeline events into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

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

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Sellsy entities map to Redash

Sellsy entityRedash objectNotes
prospectssellsy_prospectsid PK · custom fields → flattened columns for query results
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 Redash?

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

How does the Sellsy to Redash sync stay up to date?

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

Related pipelines

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