DatriseAI-first ETL

Clay to ThoughtSpot Integration

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

How Datrise loads Clay into ThoughtSpot

Datrise syncs Clay's tables, rows, enrichment runs, waterfalls, data sources, and exported lists into ThoughtSpot as warehouse tables ThoughtSpot indexes for search. Flexible or custom fields land in flattened columns for searchable fields, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the indexed tables, so re-runs update only what changed. Date-partitioned facts for live-query performance. ThoughtSpot search relies on clear names and relationships, so Datrise lands well-named, joinable tables.

Ideal for natural-language search analytics over a warehouse.

Endpoints

Clay: Data enrichment tables that build outbound lists.

ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.

How Clay entities map to ThoughtSpot

Clay entityThoughtSpot objectNotes
tablesclay_tablesid PK · custom fields → flattened columns for searchable fields
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 ThoughtSpot?

Flexible values are stored as flattened columns for searchable fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native ThoughtSpot types.

How does the Clay to ThoughtSpot sync stay up to date?

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

Related pipelines

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