DatriseAI-first ETL

Clay to Redash Integration

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

How Datrise loads Clay into Redash

Datrise syncs Clay's tables, rows, enrichment runs, waterfalls, data sources, and exported lists 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

Clay: Data enrichment tables that build outbound lists.

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

How Clay entities map to Redash

Clay entityRedash objectNotes
tablesclay_tablesid PK · custom fields → flattened columns for query results
rowsclay_rowsid PK · linked to clay_tables
enrichment runsclay_enrichment_runsid PK · linked to clay_tables
waterfallsclay_waterfallsid PK · linked to clay_tables

FAQ

How does Datrise handle Clay'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 Clay 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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