DatriseAI-first ETL

Aircall to MongoDB Integration

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

How Datrise loads Aircall into MongoDB

Datrise syncs Aircall's calls, users, teams, phone numbers, tags, and call recordings 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

Aircall: Cloud phone system for sales and support teams.

MongoDB: Document database for flexible schemas.

How Aircall entities map to MongoDB

Aircall entityMongoDB objectNotes
callsaircall_callsid PK · custom fields → native nested documents
usersaircall_usersid PK · linked to aircall_calls
teamsaircall_teamsid PK · linked to aircall_calls
phone numbersaircall_phone_numbersid PK · linked to aircall_calls

FAQ

How does Datrise handle Aircall'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 Aircall 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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