DatriseAI-first ETL

Mambu to MongoDB Integration

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

How Datrise loads Mambu into MongoDB

Datrise syncs Mambu's clients, loan accounts, deposit accounts, transactions, repayments, 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

Mambu: Cloud core banking and lending engine.

MongoDB: Document database for flexible schemas.

How Mambu entities map to MongoDB

Mambu entityMongoDB objectNotes
clientsmambu_clientsid PK · custom fields → native nested documents
loan accountsmambu_loan_accountsid PK · linked to mambu_clients
deposit accountsmambu_deposit_accountsid PK · linked to mambu_clients
transactionsmambu_transactionsid PK · linked to mambu_clients

FAQ

How does Datrise handle Mambu'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 Mambu 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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