DatriseAI-first ETL

Contentful to MongoDB Integration

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

How Datrise loads Contentful into MongoDB

Datrise syncs Contentful's entries, content types, assets, spaces, locales, and publish events 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

Contentful: Headless CMS for structured content delivery.

MongoDB: Document database for flexible schemas.

How Contentful entities map to MongoDB

Contentful entityMongoDB objectNotes
entriescontentful_entriesid PK · custom fields → native nested documents
content typescontentful_content_typesid PK · linked to contentful_entries
assetscontentful_assetsid PK · linked to contentful_entries
spacescontentful_spacesid PK · linked to contentful_entries

FAQ

How does Datrise handle Contentful'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 Contentful 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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