Everhour to MongoDB Integration
AI-first ETL from Everhour into MongoDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Everhour into MongoDB
Datrise syncs Everhour's time entries, projects, tasks, users, clients, and budgets 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
Everhour: Time tracking and budgets for project teams.
MongoDB: Document database for flexible schemas.
How Everhour entities map to MongoDB
| Everhour entity | MongoDB object | Notes |
|---|---|---|
| time entries | everhour_time_entries | id PK · custom fields → native nested documents |
| projects | everhour_projects | id PK · linked to everhour_time_entries |
| tasks | everhour_tasks | id PK · linked to everhour_time_entries |
| users | everhour_users | id PK · linked to everhour_time_entries |
FAQ
How does Datrise handle Everhour'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 Everhour 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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