Openweather to MongoDB Integration
AI-first ETL from Openweather into MongoDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Openweather into MongoDB
Datrise syncs Openweather's current conditions, forecasts, locations, temperature readings, precipitation, and observation times 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
Openweather: Current conditions and weather forecast data.
MongoDB: Document database for flexible schemas.
How Openweather entities map to MongoDB
| Openweather entity | MongoDB object | Notes |
|---|---|---|
| current conditions | openweather_current_conditions | id PK · custom fields → native nested documents |
| forecasts | openweather_forecasts | id PK · linked to openweather_current_conditions |
| locations | openweather_locations | id PK · linked to openweather_current_conditions |
| temperature readings | openweather_temperature_readings | id PK · linked to openweather_current_conditions |
FAQ
How does Datrise handle Openweather'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 Openweather to MongoDB sync stay up to date?
It runs incrementally — Datrise uses upserts by stable id with updateOne(upsert) on the source primary key.
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