Snowflake to MongoDB Integration

How Datrise loads Snowflake into MongoDB

Datrise syncs Snowflake's databases, schemas, tables, views, query history, and warehouses 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

Snowflake: Cloud data platform with separated storage and compute.

MongoDB: Document database for flexible schemas.

How Snowflake entities map to MongoDB

Snowflake entity	MongoDB object	Notes
databases	`snowflake_databases`	id PK · custom fields → native nested documents
schemas	`snowflake_schemas`	id PK · linked to snowflake_databases
tables	`snowflake_tables`	id PK · linked to snowflake_databases
views	`snowflake_views`	id PK · linked to snowflake_databases

FAQ

How does Datrise handle Snowflake'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 Snowflake 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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