Technical analysis of graph database benchmarks comparing FalkorDB and Neo4j performance metrics. FalkorDB achieves 500x faster p99 and 10x faster p50 latency in aggregate expansion operations.
Ultra-fast, multi-tenant graph database using sparse matrix representations and linear algebra, ideal for highly technical teams that handle complex data in real-time, resulting in fewer hallucinations and more accurate responses from LLMs.
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Simply ontology creation, knowledge graph creation, and agent orchestrator
Ultra-fast, multi-tenant graph database using sparse matrix representations and linear algebra, ideal for highly technical teams that handle complex data in real-time, resulting in fewer hallucinations and more accurate responses from LLMs.
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CTO at Intel Ignite Tel-Aviv
I enjoy using FalkorDB in the GraphRAG solution I'm working on.
As a developer, using graphs also gives me better visibility into what the algorithm does, when it fails, and how it could be improved. Doing that with similarity scoring is much less intuitive.
Dec 2, 2024
Ultra-fast, multi-tenant graph database using sparse matrix representations and linear algebra, ideal for highly technical teams that handle complex data in real-time, resulting in fewer hallucinations and more accurate responses from LLMs.
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