Google PageSpeed Insights to Chartio Integration

How Datrise loads Google PageSpeed Insights into Chartio

Datrise syncs Google PageSpeed Insights's audits, lab metrics, field metrics, opportunities, page URLs, and performance scores into Chartio as SQL tables a visual-SQL explorer connects to. Flexible or custom fields land in flattened columns for visual SQL, 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. Visual-SQL tools build joins from your schema, so Datrise lands clearly related tables with stable id columns.

Ideal for drag-and-drop charting over a database.

Endpoints

Google PageSpeed Insights: Page performance and Core Web Vitals audits.

Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.

How Google PageSpeed Insights entities map to Chartio

Google PageSpeed Insights entity	Chartio object	Notes
audits	`google_pagespeed_insights_audits`	id PK · custom fields → flattened columns for visual SQL
lab metrics	`google_pagespeed_insights_lab_metrics`	id PK · linked to google_pagespeed_insights_audits
field metrics	`google_pagespeed_insights_field_metrics`	id PK · linked to google_pagespeed_insights_audits
opportunities	`google_pagespeed_insights_opportunities`	id PK · linked to google_pagespeed_insights_audits

FAQ

How does Datrise handle Google PageSpeed Insights's custom fields in Chartio?

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

How does the Google PageSpeed Insights to Chartio sync stay up to date?

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

Related pipelines

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