Clay to Amazon QuickSight Integration

How Datrise loads Clay into Amazon QuickSight

Datrise syncs Clay's tables, rows, enrichment runs, waterfalls, data sources, and exported lists into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

Clay: Data enrichment tables that build outbound lists.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Clay entities map to Amazon QuickSight

Clay entity	Amazon QuickSight object	Notes
tables	`clay_tables`	id PK · custom fields → flattened columns for analyses
rows	`clay_rows`	id PK · linked to clay_tables
enrichment runs	`clay_enrichment_runs`	id PK · linked to clay_tables
waterfalls	`clay_waterfalls`	id PK · linked to clay_tables

FAQ

How does Datrise handle Clay's custom fields in Amazon QuickSight?

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

How does the Clay to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

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