Convex Dev → Redash
AI-first ETL from Convex Dev into Redash. Governed entities, incremental sync, typed landing tables.
How Datrise loads Convex Dev into Redash
Datrise syncs Convex Dev's records, events, and configuration objects 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
Convex Dev: SaaS or API data source for analytics and warehouse sync.
Redash: Open-source SQL client for queries, visualizations, and dashboards.
How Convex Dev entities map to Redash
| Convex Dev entity | Redash object | Notes |
|---|---|---|
| records | convex_dev_records | id PK · custom fields → flattened columns for query results |
| events | convex_dev_events | temporal columns events |
| configuration objects | convex_dev_configuration_objects | id PK · linked to convex_dev_records |
FAQ
How does Datrise handle Convex Dev'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 Convex Dev to Redash sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
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