DatriseAI-first ETL

Qualaroo to MongoDB Integration

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

How Datrise loads Qualaroo into MongoDB

Datrise syncs Qualaroo's surveys, responses, questions, respondents, nudges, and sentiment scores 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

Qualaroo: On-site surveys and user sentiment capture.

MongoDB: Document database for flexible schemas.

How Qualaroo entities map to MongoDB

Qualaroo entityMongoDB objectNotes
surveysqualaroo_surveysid PK · custom fields → native nested documents
responsesqualaroo_responsesid PK · linked to qualaroo_surveys
questionsqualaroo_questionsid PK · linked to qualaroo_surveys
respondentsqualaroo_respondentsid PK · linked to qualaroo_surveys

FAQ

How does Datrise handle Qualaroo'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 Qualaroo 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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