DatriseAI-first ETL

Google Pagespeed Insights Azure Synapse

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

How Datrise loads Google Pagespeed Insights into Azure Synapse

Datrise syncs Google Pagespeed Insights's records, events, and configuration objects into Azure Synapse as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses COPY into staging, then a MERGE on stable id, so re-runs update only what changed. Hash distribution on the join id with date partitioning on facts. Synapse dedicated pools reward good hash-distribution choices, so Datrise distributes on entity ids to avoid data-movement-heavy joins.

Ideal for Azure analytics estates feeding Power BI.

Endpoints

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

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Google Pagespeed Insights entities map to Azure Synapse

Google Pagespeed Insights entityAzure Synapse objectNotes
recordsgoogle_pagespeed_insights_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
eventsgoogle_pagespeed_insights_eventsdatetime2 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 Azure Synapse?

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

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

It runs incrementally — Datrise uses COPY into staging, then a MERGE on stable id.

Related pipelines

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