DatriseAI-first ETL

Listrak to MongoDB Integration

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

How Datrise loads Listrak into MongoDB

Datrise syncs Listrak's contacts, lists, campaigns, message events, orders, and segments 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

Listrak: Retail email, SMS, and behavioral marketing.

MongoDB: Document database for flexible schemas.

How Listrak entities map to MongoDB

Listrak entityMongoDB objectNotes
contactslistrak_contactsid PK · custom fields → native nested documents
listslistrak_listsid PK · linked to listrak_contacts
campaignslistrak_campaignsid PK · linked to listrak_contacts
message eventslistrak_message_eventsBSON Date events

FAQ

How does Datrise handle Listrak'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 Listrak 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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