DatriseAI-first ETL

Dolibarr to Snowflake Integration

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

How Datrise loads Dolibarr into Snowflake

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

Sync is incremental: Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size, so re-runs update only what changed. Automatic micro-partitioning, with optional clustering keys on high-cardinality ids. Snowflake upper-cases unquoted identifiers, so Datrise standardizes on lower-case quoted names to keep column references stable.

Ideal for central analytics warehouses feeding BI and AI workloads.

Endpoints

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

Snowflake: Cloud data warehouse with separated compute and storage.

How Dolibarr entities map to Snowflake

Dolibarr entitySnowflake objectNotes
third partiesdolibarr_third_partiesid PK · custom fields → VARIANT 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 Snowflake?

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

How does the Dolibarr to Snowflake sync stay up to date?

It runs incrementally — Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size.

Related pipelines

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