Everhour to Redash Integration
AI-first ETL from Everhour into Redash. Governed entities, incremental sync, typed landing tables.
How Datrise loads Everhour into Redash
Datrise syncs Everhour's time entries, projects, tasks, users, clients, and budgets into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.
Ideal for lightweight, query-driven dashboards.
Endpoints
Everhour: Time tracking and budgets for project teams.
Redash: Open-source SQL client for queries, visualizations, and dashboards.
How Everhour entities map to Redash
| Everhour entity | Redash object | Notes |
|---|---|---|
| time entries | everhour_time_entries | id PK · custom fields → flattened columns for query results |
| 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 Redash?
Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.
How does the Everhour to Redash sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
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