DatriseAI-first ETL

Visma e-conomic to MongoDB Integration

AI-first ETL from Visma e-conomic into MongoDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads Visma e-conomic into MongoDB

Datrise syncs Visma e-conomic's invoices, customers, suppliers, journal entries, accounts, and products into MongoDB as a collection per source entity. Flexible or custom fields land in native nested documents, and timestamps such as created, updated, and status changes are typed as BSON Date.

Sync is incremental: Datrise uses upserts by stable id with updateOne(upsert) on the source primary key, so re-runs update only what changed. Optional sharding on the entity id for large collections. Mongo has no fixed schema, so Datrise keeps field types consistent across documents to avoid mixed-type query surprises.

Ideal for document-oriented apps that want CRM data in their existing Mongo store.

Endpoints

Visma e-conomic: Nordic accounting, invoicing, and ledger records.

MongoDB: Document database for flexible schemas.

How Visma e-conomic entities map to MongoDB

Visma e-conomic entityMongoDB objectNotes
invoicesvisma_e_conomic_invoicesid PK · custom fields → native nested documents
customersvisma_e_conomic_customersid PK · linked to visma_e_conomic_invoices
suppliersvisma_e_conomic_suppliersid PK · linked to visma_e_conomic_invoices
journal entriesvisma_e_conomic_journal_entriesid PK · linked to visma_e_conomic_invoices

FAQ

How does Datrise handle Visma e-conomic's custom fields in MongoDB?

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

How does the Visma e-conomic to MongoDB sync stay up to date?

It runs incrementally — Datrise uses upserts by stable id with updateOne(upsert) on the source primary key.

Related pipelines

Early access

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