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FalkorDB Knowledge Graph DBMS — Startup Profile
Startup

FalkorDB Knowledge Graph DBMS

We Make AI Reliable | Low-latency, Redis-powered Architecture | GraphRAG

Data & AnalyticsEstimated

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GitHub stars: falkordb/falkordb02.5k5k7.5k10kJul 2023Aug 2024Sep 2025Oct 2026
GitHub stars: falkordb/falkordb, last 12 months02.5k5k7.5k10kOct 2025Feb 2026Jun 2026Oct 2026
GitHub stars: falkordb/falkordb, last 90 days02.5k5k7.5k10k15 Jul14 Aug12 Sep12 Oct

9,287 GitHub stars

+7 days
+1,768
+30 days
+3,264
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[![FalkorDB Knowledge Graph DBMS on Astracia](https://astracia.com/signals/open-source/badge/709900.svg)](https://astracia.com/startups/709900/falkordb-knowledge-graph-dbms)

Data: GitHub API

About the startup

FalkorDB provides a unified solution that seamlessly integrates the capabilities of Knowledge Graphs and Vector Databases. Its low-latency is designed to efficiently handle both graph traversal and vector similarity searches, thus eliminating the need for separate systems and reducing integration complexity. By leveraging FalkorDB, organizations can overcome the challenges of integrating Knowledge Graphs with Vector Databases, enabling the development of sophisticated AI applications that are both reliable and efficient. FalkorDB already works seamlessly with technologies like LangChain, Diffbot API, OpenAI, and LLMs like the Llama or Mistral series. For instance, when developing a RAG application, you can use FalkorDB to construct a Knowledge Graph from diverse documents, which can then serve as a rich contextual base for LLMs to generate more informed and precise answers. This approach not only enhances the capabilities of LLMs but also mitigates common issues like hallucinations by providing a solid factual foundation from the Knowledge Graphs.

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