Google Pagespeed Insights → PostgreSQL

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

How Datrise loads Google Pagespeed Insights into PostgreSQL

Datrise syncs Google Pagespeed Insights's records, events, and configuration objects into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Google Pagespeed Insights: SaaS or API data source for analytics and warehouse sync.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Google Pagespeed Insights entities map to PostgreSQL

Google Pagespeed Insights entity	PostgreSQL object	Notes
records	`google_pagespeed_insights_records`	id PK · custom fields → jsonb columns
events	`google_pagespeed_insights_events`	timestamptz events
configuration objects	`google_pagespeed_insights_configuration_objects`	id PK · linked to google_pagespeed_insights_records

FAQ

How does Datrise handle Google Pagespeed Insights's custom fields in PostgreSQL?

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

How does the Google Pagespeed Insights to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

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Connect Google Pagespeed Insights to PostgreSQL the easy way

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