DatriseAI-first ETL

Firebase to MongoDB Integration

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

How Datrise loads Firebase into MongoDB

Datrise syncs Firebase's users, collections, documents, auth events, app events, and security rules 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

Firebase: App backend with auth, storage, and analytics.

MongoDB: Document database for flexible schemas.

How Firebase entities map to MongoDB

Firebase entityMongoDB objectNotes
usersfirebase_usersid PK · custom fields → native nested documents
collectionsfirebase_collectionsid PK · linked to firebase_users
documentsfirebase_documentsid PK · linked to firebase_users
auth eventsfirebase_auth_eventsBSON Date events

FAQ

How does Datrise handle Firebase'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 Firebase 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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