DatriseAI-first ETL

Auth0 MongoDB

AI-first ETL from Auth0 into MongoDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads Auth0 into MongoDB

Datrise syncs Auth0's authentication logs, sign-ins, user identity changes, and security events 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

Auth0: Identity source for authentication and sign-in telemetry.

MongoDB: Document database for flexible schemas.

How Auth0 entities map to MongoDB

Auth0 entityMongoDB objectNotes
authentication logsauth0_authentication_logsid PK · custom fields → native nested documents
sign-insauth0_sign_insid PK · linked to auth0_authentication_logs
user identity changesauth0_user_identity_changesBSON Date events
security eventsauth0_security_eventsBSON Date events

FAQ

How does Datrise handle Auth0'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 Auth0 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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