Lightning-Fast Graph Analytics for Data Science & AI
Get answers in milliseconds from the fastest columnar in-memory graph database engine, featuring git-like versioning. In a critical industry that needs fast, auditable AI systems? Build truly responsive analytical products with TuringDB.
Trusted & supported by world-class teams
Low-latency queries
Get complex graph query responses in milliseconds, for a smooth, fast User Experience (UX). Build faster analytics, simulations, and AI systems
No reads & writes competition
Zero-lock concurrency ensures your reads and writes never compete, so your analytics are never slowed down by your data inputs
Full snapshot isolation
The immutable snapshots ensure that specific versions of your graph remain the same and cannot be changed, critical for reproducibility & auditability
Git-like versioning
Reduce maintenance complexities with auditable graphs: create and commit versions, keep different versions in branches, merge in main, and time travel
Rich metadata for AI
Nodes & edges can store rich metadata with unlimited properties, perfect for digital twins or for LLMs and agentic AI systems that need context
Compatible with Cypher
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
Low-latency at scale
Get ultra-fast queries on large graphs, especially on multi-hop and deep traversals
TuringDB offers:
- Real time UX for AI apps & analytics
- Instant access to complex connected data
- 1-50ms latencies at scale
- 200x to 4000x greater speed than Neo4J
Time Travel and Git-like Versioning
TuringDB stores every change ever made to your graphs using git-like versioning as an immutable commit.
- Query any version of your graph at full speed
- Branch & merge graph databases for what-if exploration without risk
- Leverage powerful time-travelling analytics and strong audit trails of changes
Zero-Lock Concurrency
TuringDB eliminates the plague of locking read transactions. Our unique architecture ensures that analytics queries are never blocked by write transactions, achieving extreme read concurrency.
- Each transaction executes on its own immutable snapshot of the database at a defined point in time
- Massive parallelism for dashboards, AI pipelines & batch analytics
- Snapshot isolation, at no cost to performance
Rich Metadata for AI & Digital Twins
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.
- Store unlimited properties on nodes and edges with rich metadata (up to 1Mb/node)
- Add large text chunks and numerical values to properties for comprehensive context
- Extract subgraphs as graph models, and enrich graph paths with metadata for LLM/agent reasoning
- Build multilayer graphs and digital twins for complex knowledge representation
Graph Node Example: Factory Equipment with Rich Metadata
In-Memory Column-Oriented Engine
Every dataset lives in RAM, eliminating I/O bottlenecks and delivering sub-millisecond graph traversals across millions of nodes and edges.
- Efficient memory packing allows large graphs to fit in standard RAM
- Transient data processing complies with GDPR and "right to be forgotten"
- Instant erasure & isolation with memory flushing leaves no traces of personal data
- Fine-grained data residency control minimises cross-border transfer risk
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