DatriseAI-first ETL

Club Speed to MongoDB Integration

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

How Datrise loads Club Speed into MongoDB

Datrise syncs Club Speed's customers, races, bookings, products, transactions, and memberships 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

Club Speed: Venue management for karting and entertainment centers.

MongoDB: Document database for flexible schemas.

How Club Speed entities map to MongoDB

Club Speed entityMongoDB objectNotes
customersclubspeed_customersid PK · custom fields → native nested documents
racesclubspeed_racesid PK · linked to clubspeed_customers
bookingsclubspeed_bookingsid PK · linked to clubspeed_customers
productsclubspeed_productsid PK · linked to clubspeed_customers

FAQ

How does Datrise handle Club Speed'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 Club Speed 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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