Harvest → Redash
AI-first ETL from Harvest into Redash. Governed entities, incremental sync, typed landing tables.
How Datrise loads Harvest into Redash
Datrise syncs Harvest's time entries, projects, clients, invoices, and utilization 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
Harvest: Time tracking and project profitability for services teams.
Redash: Open-source SQL client for queries, visualizations, and dashboards.
How Harvest entities map to Redash
| Harvest entity | Redash object | Notes |
|---|---|---|
| time entries | harvest_time_entries | id PK · custom fields → flattened columns for query results |
| projects | harvest_projects | id PK · linked to harvest_time_entries |
| clients | harvest_clients | id PK · linked to harvest_time_entries |
| invoices | harvest_invoices | id PK · linked to harvest_time_entries |
FAQ
How does Datrise handle Harvest'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 Harvest to Redash sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Harvest
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