Interactive Demos
Explore 3D graph visualizations powered by real-world datasets. Rotate, zoom, and click nodes to inspect properties.
The hop-depth ceiling, demolished. Industry consensus says graph traversal beyond 3-5 hops is “computationally infeasible” (arXiv 2511.19648, November 2025). Neo4j’s own ICIJ reference example caps at 5 hops. TigerGraph publishes a 10-hop ceiling. Money launderers know all of this — that’s exactly why their shell-company chains run 6, 10, 15 layers deep. We just walked 15 hops through the Panama Papers in 437 ms.
ICIJ Offshore Leaks — 15-Hop Live Walk
2 million ICIJ nodes • 3.3 million edges • named-entity reveals (Putin/Roldugin shell network, Sharif/Avenfield apartments, Mossack Fonseca’s deepest chains) • live CPU/RAM/latency counters from the actual rental box during the query
Launch Live Demo
Bonus benchmark on the same data:
5.3 million graph elements ingested from an empty container in ~6 minutes
(2M nodes via BULK_UPSERT_NODES, 3.3M edges via BULK_INSERT_EDGES_KEYED @ 66,000 edges/sec)
— less time than a coffee break, vs. the 12+ hours the equivalent Cypher MATCH+CREATE batches take.
The drop-and-reload story for v5.
Live ADS-B aircraft data from 24 US regions. xrayGraphDB predicts where each aircraft should be before the next update, compares prediction to reality, learns route patterns by flight number, and flags deviations — all at 286K+ peak QPS on our patent-pending engine. 5,000+ aircraft tracked simultaneously with <1% CPU usage.
Realtime Predictive Airspace
5,000+ aircraft • Route envelope learning • CYP deviation scoring • Flight instruments • 60fps canvas rendering • WebSocket push
Launch Live DemoDrop in a patient's full medication list. In under 1 millisecond, xrayGraphDB maps every drug-drug interaction, every CYP450 enzyme conflict, every cascade risk — and tells you which single medication change reduces the most risk. 1,933 real drugs, 149,361 real interactions, 14 metabolic enzymes. Powered by our patent-pending graph engine — answers no lookup table can replicate.
Polypharmacy Interaction Analyzer
Full interaction graph • CYP450 enzyme load map • Cascade detection • Optimal removal analysis • Alternative finder • Sub-millisecond
Launch Live DemoTechnology demonstration only. Not a clinical tool.
Real exoplanet data from the NASA Exoplanet Archive and JWST atmospheric detections. This demo shows how xrayGraphDB's patent-pending engine handles multi-dimensional scientific queries — combining stellar properties, planetary parameters, and atmospheric composition in real-time queries that would require complex JOIN chains in traditional databases.
Live Query Panel
NASA ExoplanetsA drug-drug interaction network based on the STRING database schema, showing ~50 real compounds from cancer signaling, DNA repair, and apoptosis pathways. Edge thickness reflects interaction confidence scores (0-999). Hover over edges to see interaction type and confidence. Try the full Polypharmacy →
Demo Queries
MATCH (p:Protein {name: "TP53"})-[r:INTERACTS_WITH]->(n)
RETURN p.name, n.name, r.score ORDER BY r.score DESCMATCH path = (p:Protein {name: "TP53"})-[:INTERACTS_WITH*1..5]->(n)
RETURN DISTINCT n.name, length(path) AS hopsMATCH (p)-[r:INTERACTS_WITH]->(n)
WHERE r.score > 900
RETURN p.name, n.name, r.scoreMATCH (drug_target)-[:INTERACTS_WITH*1..4]->(disease_protein)
WHERE disease_protein.name = "BRCA1"
RETURN DISTINCT drug_target.nameMATCH (p:Protein)
WITH p, EMBED(p.function) AS vec
RETURN p.name, p.function
ORDER BY cosine_similarity(vec, EMBED("DNA repair")) DESC LIMIT 10Live Query Panel
Connected to xrayGraphDBLive Bitcoin blockchain analysis with real-time fraud detection. Every unconfirmed transaction analyzed in milliseconds by xrayGraphDB's patent-pending engine, which breaks the 10+ hop barrier that stops traditional graph databases.
Bitcoin Mainnet — Live
Real-time on-chain analysis with 3D force-directed graph visualization,
taint propagation, CoinJoin detection, and OFAC sanctions proximity alerts.