Google Cloud Storage to MongoDB Integration

How Datrise loads Google Cloud Storage into MongoDB

Datrise syncs Google Cloud Storage's buckets, objects, prefixes, object metadata, generations, and storage classes 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

Google Cloud Storage: Object storage for files and data lake exports on GCP.

MongoDB: Document database for flexible schemas.

How Google Cloud Storage entities map to MongoDB

Google Cloud Storage entity	MongoDB object	Notes
buckets	`google_cloud_storage_f_buckets`	id PK · custom fields → native nested documents
objects	`google_cloud_storage_f_objects`	id PK · linked to google_cloud_storage_f_buckets
prefixes	`google_cloud_storage_f_prefixes`	id PK · linked to google_cloud_storage_f_buckets
object metadata	`google_cloud_storage_f_object_metadata`	id PK · linked to google_cloud_storage_f_buckets

FAQ

How does Datrise handle Google Cloud Storage'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 Google Cloud Storage 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

Connect Google Cloud Storage to MongoDB the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.