Google PageSpeed Insights to Amazon Redshift Integration
AI-first ETL from Google PageSpeed Insights into Amazon Redshift. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google PageSpeed Insights into Amazon Redshift
Datrise syncs Google PageSpeed Insights's audits, lab metrics, field metrics, opportunities, page URLs, and performance scores into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.
Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.
Ideal for AWS-native warehouses already using the Redshift ecosystem.
Endpoints
Google PageSpeed Insights: Page performance and Core Web Vitals audits.
Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.
How Google PageSpeed Insights entities map to Amazon Redshift
| Google PageSpeed Insights entity | Amazon Redshift object | Notes |
|---|---|---|
| audits | google_pagespeed_insights_audits | id PK · custom fields → SUPER 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 Amazon Redshift?
Flexible values are stored as SUPER columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Redshift types.
How does the Google PageSpeed Insights to Amazon Redshift sync stay up to date?
It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.
Related pipelines
More destinations for Google PageSpeed Insights
- Google PageSpeed Insights → Databricks SQL Warehouse
- Google PageSpeed Insights → ClickHouse
- Google PageSpeed Insights → DuckDB
- Google PageSpeed Insights → Amazon Athena
- Google PageSpeed Insights → Amazon S3 Data Lake
- Google PageSpeed Insights → Azure Data Lake Storage
- Google PageSpeed Insights → Azure Synapse
- Google PageSpeed Insights → Spreadsheets
- Google PageSpeed Insights → Airtable
- Google PageSpeed Insights → CSV Files
- Google PageSpeed Insights → MongoDB
- Google PageSpeed Insights → Supabase
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Early access
Connect Google PageSpeed Insights to Amazon Redshift the easy way
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