DatriseAI-first ETL

Visma E Conomic MongoDB

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 records, events, and configuration objects 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: SaaS or API data source for analytics and warehouse sync.

MongoDB: Document database for flexible schemas.

How Visma E Conomic entities map to MongoDB

Visma E Conomic entityMongoDB objectNotes
recordsvisma_e_conomic_recordsid PK · custom fields → native nested documents
eventsvisma_e_conomic_eventsBSON Date events
configuration objectsvisma_e_conomic_configuration_objectsid PK · linked to visma_e_conomic_records

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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