DatriseAI-first ETL

Google Pagespeed Insights Redash

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

How Datrise loads Google Pagespeed Insights into Redash

Datrise syncs Google Pagespeed Insights's records, events, and configuration objects into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, 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 for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

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

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Google Pagespeed Insights entities map to Redash

Google Pagespeed Insights entityRedash objectNotes
recordsgoogle_pagespeed_insights_recordsid PK · custom fields → flattened columns for query results
eventsgoogle_pagespeed_insights_eventstemporal columns events
configuration objectsgoogle_pagespeed_insights_configuration_objectsid PK · linked to google_pagespeed_insights_records

FAQ

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

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

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

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

Related pipelines

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