Google PageSpeed Insights to MySQL Integration

AI-first ETL from Google PageSpeed Insights into MySQL. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google PageSpeed Insights into MySQL

Datrise syncs Google PageSpeed Insights's audits, lab metrics, field metrics, opportunities, page URLs, and performance scores into MySQL as a typed table per source entity. Flexible or custom fields land in JSON columns, and timestamps such as created, updated, and status changes are typed as DATETIME/TIMESTAMP.

Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE, so re-runs update only what changed. Optional RANGE partitioning by load date. MySQL collation matters for CRM text, so Datrise lands utf8mb4 to preserve emoji and non-Latin characters.

Ideal for operational reporting and app databases already standardized on MySQL.

Endpoints

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

MySQL: Widely used OSS relational engine (InnoDB).

How Google PageSpeed Insights entities map to MySQL

Google PageSpeed Insights entity	MySQL object	Notes
audits	`google_pagespeed_insights_audits`	id PK · custom fields → JSON columns
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 MySQL?

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

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

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE.

Related pipelines

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