Pirsch Analytics vs BigQuery
Side-by-side trajectory, velocity, and editorial themes.
Pirsch ships a tight maintenance cadence — bot filtering, dashboard polish, and dependency hygiene.
Pirsch is releasing every few days with very small payloads. The April cluster centers on bot detection — improved filters in 2.14.10 and 2.14.12, plus a referrer-parameter bot fix in 2.14.11. March added dashboard creation settings, an option to hide the UTM panel, expiration times on access links, and a referrer blacklist update. Earlier in February, email reports gained a start date and the Fathom Analytics importer was updated.
Pirsch is in steady operational mode — defending against bots, polishing dashboard surfaces, and keeping dependencies current. The Fathom importer updates and email-report work are the only signs of growth-oriented investment; otherwise the cadence is custodial. The product feels like it's competing on reliability and privacy rather than feature surface.
Expect bot-filter work to continue (this is an arms race for any analytics provider) and the Fathom importer to keep getting attention as Fathom users churn. Larger directional moves aren't visible in the feed; the next signal would be a real new product surface — funnels v2, server-side eventing, or an AI insights panel.
BigQuery doubles down on Iceberg, graph, and global data sharing as the lakehouse fight intensifies.
BigQuery's May 2026 ship list is dominated by three tracks: open-format lakehouse integration (Iceberg v3 with deletion vectors, REST catalog support in Conversational Analytics), graph capabilities maturing inside BigQuery Studio, and global data exchange via multi-region sharing listings reaching GA. Alongside the feature work, Google is tightening Data Transfer Service security (MFA on Google Ads transfers) and warning about Ads retention changes that will cap historical backfills from June 1. The release notes show a mature warehouse continuing to absorb adjacent workloads rather than reinventing itself.
BigQuery is positioning itself as the federated query and sharing fabric for a multi-format world, with Iceberg getting closer to first-class status and Conversational Analytics extending across external catalogs. The graph and notebook work signals a push to keep more analytical work inside Studio instead of bouncing to specialized tools. Expect continued layering of governance, AI-assisted query, and open-table support on top of the existing engine rather than core engine reinvention.
Next obvious step is GA for Iceberg v3 features and full conversational graph querying without Preview gating. Watch for additional first-party data sources getting MFA mandates, mirroring the Google Ads tightening.
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