DatriseAI-first ETL

Megaplan MongoDB

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

How Datrise loads Megaplan into MongoDB

Datrise syncs Megaplan's contacts, accounts, deals, activities, and lifecycle events 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

Megaplan: CRM with strong adoption in CIS markets for sales and operations.

MongoDB: Document database for flexible schemas.

How Megaplan entities map to MongoDB

Megaplan entityMongoDB objectNotes
contactsmegaplan_contactsid PK · custom fields → native nested documents
accountsmegaplan_accountsid PK · linked to megaplan_contacts
dealsmegaplan_dealsid PK · linked to megaplan_contacts
activitiesmegaplan_activitiesBSON Date events

FAQ

How does Datrise handle Megaplan'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 Megaplan 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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