DatriseAI-first ETL

Dolibarr to Amazon Redshift Integration

AI-first ETL from Dolibarr into Amazon Redshift. Governed entities, incremental sync, typed landing tables.

How Datrise loads Dolibarr into Amazon Redshift

Datrise syncs Dolibarr's third parties, proposals, orders, invoices, contracts, and interventions into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.

Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.

Ideal for AWS-native warehouses already using the Redshift ecosystem.

Endpoints

Dolibarr: Open-source ERP and CRM for small organizations.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Dolibarr entities map to Amazon Redshift

Dolibarr entityAmazon Redshift objectNotes
third partiesdolibarr_third_partiesid PK · custom fields → SUPER columns
proposalsdolibarr_proposalsid PK · linked to dolibarr_third_parties
ordersdolibarr_ordersid PK · linked to dolibarr_third_parties
invoicesdolibarr_invoicesid PK · linked to dolibarr_third_parties

FAQ

How does Datrise handle Dolibarr's custom fields in Amazon Redshift?

Flexible values are stored as SUPER columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Redshift types.

How does the Dolibarr to Amazon Redshift sync stay up to date?

It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.

Related pipelines

Early access

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