DatriseAI-first ETL

JobAdder to MongoDB Integration

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

How Datrise loads JobAdder into MongoDB

Datrise syncs JobAdder's candidates, jobs, applications, placements, companies, and interview notes 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

JobAdder: Recruitment platform for job ads, applications, and placements.

MongoDB: Document database for flexible schemas.

How JobAdder entities map to MongoDB

JobAdder entityMongoDB objectNotes
candidatesjobadder_candidatesid PK · custom fields → native nested documents
jobsjobadder_jobsid PK · linked to jobadder_candidates
applicationsjobadder_applicationsid PK · linked to jobadder_candidates
placementsjobadder_placementsid PK · linked to jobadder_candidates

FAQ

How does Datrise handle JobAdder'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 JobAdder 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

Early access

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