Connect Matomo to PostgreSQL

Connect Matomo and add PostgreSQL as the stored destination. Create a datastream, then save a job that sends the required records to the "sessions" table.

Select concrete Matomo fields such as Distinct campaigns, Distinct keywords, Distinct search engines, and Date. You can rename the chosen columns, preview the result, and write them to PostgreSQL tables such as properties, sessions, and users.

Choose how far back the first Matomo load should go and how much recent data each "sessions" run should refresh. Catchr splits large backfills into smaller intervals.

For recurring Matomo loads, assign an eligible partition field to "sessions". Otherwise Catchr cannot match the refresh window and will append the returned records.

With Matomo data, a PostgreSQL query can summarize users, sessions, conversions, and conversion rate by traffic source. Join Distinct campaigns and Distinct keywords with shared account or date keys to build a reusable performance model in PostgreSQL.

Yes. Connect an existing PostgreSQL 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.