Everhour to Apache Superset Integration
AI-first ETL from Everhour into Apache Superset. Governed entities, incremental sync, typed landing tables.
How Datrise loads Everhour into Apache Superset
Datrise syncs Everhour's time entries, projects, tasks, users, clients, and budgets into Apache Superset as governed SQL tables Superset queries directly. Flexible or custom fields land in flattened columns for the explore UI, and timestamps such as created, updated, and status changes are typed as temporal columns for time-series charts.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned tables to keep dashboards responsive. Superset charts run live SQL, so Datrise lands query-friendly, indexed tables rather than wide raw payloads.
Ideal for open-source dashboards over your own database.
Endpoints
Everhour: Time tracking and budgets for project teams.
Apache Superset: Open-source BI for SQL exploration, charts, and dashboard publishing.
How Everhour entities map to Apache Superset
| Everhour entity | Apache Superset object | Notes |
|---|---|---|
| time entries | everhour_time_entries | id PK · custom fields → flattened columns for the explore UI |
| 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 Apache Superset?
Flexible values are stored as flattened columns for the explore UI, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Apache Superset types.
How does the Everhour to Apache Superset sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
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Early access
Connect Everhour to Apache Superset the easy way
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