DatriseAI-first ETL

Localytics to MongoDB Integration

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

How Datrise loads Localytics into MongoDB

Datrise syncs Localytics's sessions, events, users, campaigns, push deliveries, and app profiles 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

Localytics: Mobile app analytics and push engagement.

MongoDB: Document database for flexible schemas.

How Localytics entities map to MongoDB

Localytics entityMongoDB objectNotes
sessionslocalytics_sessionsid PK · custom fields → native nested documents
eventslocalytics_eventsBSON Date events
userslocalytics_usersid PK · linked to localytics_sessions
campaignslocalytics_campaignsid PK · linked to localytics_sessions

FAQ

How does Datrise handle Localytics'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 Localytics 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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