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Comparison · Analytics

Pirsch Analytics vs Neo4j

Side-by-side trajectory, velocity, and editorial themes.

P3.8

Pirsch ships a tight maintenance cadence — bot filtering, dashboard polish, and dependency hygiene.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

N
Neo4j
ANALYTICS
6.3

neo4j-cli ships explicitly for AI agents — Neo4j makes its 'AX' bet concrete.

◆ Current state

Neo4j is shipping in three lanes simultaneously: developer/agent surface (the new neo4j-cli covering Aura management, Cypher, and ops, designed for human, developer and agent consumption), Aura cloud capacity and ops (2TB high-memory GCP instances, inactive-member pruning, tighter password policy), and graph analytics maturation (project-level ML model persistence in AGA, Lakehouse export from Microsoft Fabric, Cypher 25 GQL features). Dashboards and Explore are gaining interactivity in parallel.

◆ Where it's heading

The arc is toward treating AI agents as a first-class user of the platform, not an integration consumer. Calling out 'AX' alongside DX/UX in the CLI announcement is unusual — most database vendors are still adding MCP servers or chat assistants. Coupled with the GenAI token functions in the April Aura release and AGA's model persistence, Neo4j is consolidating the 'graph as memory substrate for AI agents' position it's been telegraphing for two years.

◆ Prediction

Likely next: an MCP server fronting the same surface as neo4j-cli, deeper GenAI-native primitives in Cypher 25 (vector ops, embeddings as first-class types), and continued Aura capacity climbs to support larger graph-RAG workloads. Microsoft Fabric integration will probably extend further given the bidirectional Lakehouse work.

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