DatriseAI-first ETL

Manatal to MongoDB Integration

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

How Datrise loads Manatal into MongoDB

Datrise syncs Manatal's candidates, jobs, applications, pipeline stages, match scores, and clients 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

Manatal: AI recruitment software with candidate scoring.

MongoDB: Document database for flexible schemas.

How Manatal entities map to MongoDB

Manatal entityMongoDB objectNotes
candidatesmanatal_candidatesid PK · custom fields → native nested documents
jobsmanatal_jobsid PK · linked to manatal_candidates
applicationsmanatal_applicationsid PK · linked to manatal_candidates
pipeline stagesmanatal_pipeline_stagesid PK · linked to manatal_candidates

FAQ

How does Datrise handle Manatal'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 Manatal 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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