DatriseAI-first ETL

Moskit CRM to MongoDB Integration

AI-first ETL from Moskit CRM into MongoDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads Moskit CRM into MongoDB

Datrise syncs Moskit CRM's contacts, companies, deals, funnel stages, tasks, and sales goals 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

Moskit CRM: Sales CRM for Brazilian inside-sales teams.

MongoDB: Document database for flexible schemas.

How Moskit CRM entities map to MongoDB

Moskit CRM entityMongoDB objectNotes
contactsmoskit_contactsid PK · custom fields → native nested documents
companiesmoskit_companiesid PK · linked to moskit_contacts
dealsmoskit_dealsid PK · linked to moskit_contacts
funnel stagesmoskit_funnel_stagesid PK · linked to moskit_contacts

FAQ

How does Datrise handle Moskit CRM'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 Moskit CRM 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

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