The fastest in-memory graph database for healthcare, finance, supply chains, and operational intelligence.












Get complex graph query responses in milliseconds, for a smooth, fast User Experience (UX). Build faster analytics, simulations, and AI systems
Zero-lock concurrency ensures your reads and writes never compete, so your analytics are never slowed down by your data inputs
The immutable snapshots ensure that specific versions of your graph remain the same and cannot be changed, critical for reproducibility & auditability
Reduce maintenance complexities with auditable graphs: create and commit versions, keep different versions in branches, merge in main, and time travel
Nodes & edges can store rich metadata with unlimited properties, perfect for digital twins or for LLMs and agentic AI systems that need context
No need to learn a new language, rewrite your current queries, or use query writing LLMs: simply use Cypher to query TuringDB graphs at scale
TuringDB's columnar in-memory architecture delivers lightning-fast graph traversals that outperform traditional databases by orders of magnitude. Run complex multi-hop queries on billion-node graphs in milliseconds, not seconds.
111,532,358 nodes · 1,615,685,872 edges
Store every change as an immutable commit. Query any version at full speed. Branch and merge for risk-free exploration with powerful time-travel analytics and complete audit trails.
TuringDB can store unlimited properties on nodes and edges along with large chunks of text and numerical values. Perfect for feeding LLMs and AI agents with context, building multilayer graphs, and creating graph-based digital twins for data and knowledge representation.
Click on any unit to view its metadata
High-pressure steam turbine installed in 2018. Critical component for power generation. Requires specialized maintenance team. Connected to boiler B-12 and generator G-5 with a 99.2% uptime...
Our engineers are experienced in helping companies integrate and get the most out of TuringDB. Schedule a call to discuss data modeling, query optimization, infrastructure requirements, or database migration.