DatriseAI-first ETL

Impact to Redash Integration

AI-first ETL from Impact into Redash. Governed entities, incremental sync, typed landing tables.

How Datrise loads Impact into Redash

Datrise syncs Impact's partners, actions, clicks, conversions, payouts, and campaigns 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

Impact: Partnership and affiliate performance tracking.

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Impact entities map to Redash

Impact entityRedash objectNotes
partnersimpact_partnersid PK · custom fields → flattened columns for query results
actionsimpact_actionsid PK · linked to impact_partners
clicksimpact_clicksid PK · linked to impact_partners
conversionsimpact_conversionsid PK · linked to impact_partners

FAQ

How does Datrise handle Impact'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 Impact to Redash sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

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