Postmark to MongoDB Integration

How Datrise loads Postmark into MongoDB

Datrise syncs Postmark's messages, servers, delivery events, bounces, opens, and message streams 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

Postmark: Transactional email delivery with detailed events.

MongoDB: Document database for flexible schemas.

How Postmark entities map to MongoDB

Postmark entity	MongoDB object	Notes
messages	`postmark_app_messages`	id PK · custom fields → native nested documents
servers	`postmark_app_servers`	id PK · linked to postmark_app_messages
delivery events	`postmark_app_delivery_events`	BSON Date events
bounces	`postmark_app_bounces`	id PK · linked to postmark_app_messages

FAQ

How does Datrise handle Postmark'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 Postmark 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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