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Comparison · Analytics

Whatagraph vs Neo4j

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

W
Whatagraph
ANALYTICS
5.0

Whatagraph is quietly building a data layer beneath its agency reporting tool.

◆ Current state

Whatagraph remains an agency-focused marketing reporting platform, but recent releases push two fronts at once: deeper data infrastructure and broader visualization. The Data Storage destination and Snowflake source let it ingest and retain data rather than just pull live API calls each render, while a steady stream of widgets (GeoMap, Gauge, Heatmap) and table controls sharpen the reporting surface clients see. Integration breadth keeps widening with WhatConverts, Shopify collaborator access, and a rebuilt CallTrackingMetrics.

◆ Where it's heading

The center of gravity is shifting from a connector that visualizes marketing channels toward a data layer that stores and blends first-party and warehouse data. Storage, 24-month backfill, and Snowflake ingestion all reduce dependence on live API calls and position Whatagraph to own more of the pipeline. Visualization work continues in parallel but increasingly reads as table-stakes polish next to the infrastructure bets.

◆ Prediction

Expect the storage and warehouse thread to deepen, with more destinations, longer retention, and richer blended-attribution tooling on the Max plan. AI-assisted report creation (Create with IQ) is the likely next surface to expand.

N
Neo4j
ANALYTICS
6.3

Neo4j Aura pushes on billing transparency, scale ceilings, and graph analytics.

◆ Current state

Neo4j's Aura cloud is shipping across three fronts: a new self-service billing experience and Billing API, higher scale ceilings (5TB storage on AWS, 2TB high-memory on GCP), and graph-analytics depth (Native Projections, ML model persistence). The monthly Aura release rolls these up with Cypher 25 GQL compliance work.

◆ Where it's heading

Aura is maturing as an enterprise managed service — financial controls, larger instances, and operational hygiene (user pruning) — while continuing to invest in the graph-data-science layer that differentiates it.

◆ Prediction

Expect continued enterprise-readiness work (billing, scale, governance) alongside GDS and GQL-compliance progress; a unified neo4j-cli also suggests more developer-CLI investment ahead.

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