Connect Google Page Speed to Azure SQL

Start with a connected Google Page Speed source and an existing Azure SQL database. Create a datastream between them, then configure the accounts, fields, schedule, and "performance scores" table.

Select concrete Google Page Speed fields such as Accessibility score, Best Practices score, Bootup Time, and Day of the month. You can rename the chosen columns, preview the result, and write them to Azure SQL tables such as sites, pages, and devices.

Set an initial fetch period for Google Page Speed, then choose the frequency and lookback window for the job writing to "performance scores". Catchr rewrites that selected period on each run.

The partition field tells Catchr which Google Page Speed rows in "performance scores" belong to the period being refreshed. If you omit it, every run appends records rather than updating them.

With Google Page Speed data, an Azure SQL query can summarize performance, accessibility, and Core Web Vitals by page. A query built around Accessibility score and Best Practices score can support trend reviews, account comparisons, and operational reporting.

Yes. Connect an existing Azure SQL  database first. The Catchr job creates and populates the destination table you configure inside that database.

Yes. Create a separate datastream and job for each source, write each export to its own table, then combine the data downstream with SQL, views, or your BI tool.