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Hosted by FalkorDB · 🇺🇸 US · EN · 16 episodes
Established thought leaders with verified media credentials.
Welcome to the FalkorDB Podcast, where we dive deep into the world of graph databases, AI-driven applications, and cutting-edge data technology. Hosted by industry veterans, this podcast brings you conversations with leading developers, innovators, and thought leaders who are shaping the future of knowledge graphs and retrieval-augmented generation (RAG).Explore real-world applications of graph technology, discover how FalkorDB is revolutionizing enterprise data infrastructure, and learn how companies are leveraging AI and machine learning to build smarter, faster systems.
FalkorDB hosts FalkorDB Podcast: Innovating at the Intersection of Graphs, AI, and Databases, a technology show with 16 episodes published.
FalkorDB GraphRAG SDK 1.0 is the #1 ranked open-source framework on GraphRAG-Bench, outperforming Microsoft and LightRAG by over 14 points. https://github.com/FalkorDB/graphRAG-SDK
Modern GraphRAG frameworks like Fast GraphRAG , LightRAG , and KET-RAG utilize graph structures to improve retrieval accuracy and cost-efficiency. Tools like StructRAG , HippoRAG 2 , and G-reasoner further enhance LLM re
NoSQL databases offer flexible alternatives to traditional relational databases for managing large, diverse, and rapidly changing data. The article highlights the limitations of SQL databases in modern, high-velocity dat
https://www.falkordb.com/news-updates/graphrag-sdk-0-5-knowledge-graph-integration/ These sources detail FalkorDB, a graph database, highlighting its performance advantages over Neo4j, particularly in aggregate expansion
https://www.falkordb.com/blog/understanding-ontologies-knowledge-graph-schemas/ This article explains ontologies and knowledge graphs, emphasizing their interconnectedness. Ontologies are defined as conceptual blueprints
Read: https://www.falkordb.com/blog/ai-agents-memory-systems/ This article explores AI agents, autonomous systems capable of making decisions and completing tasks. It details the evolution of AI agents, from reactive to
Ref: https://www.falkordb.com/blog/llamaindex-rag-implementation-graphrag/ This article explains how to build efficient Retrieval Augmented Generation (RAG) systems using LlamaIndex and FalkorDB. LlamaIndex is an open-s
Ref: https://www.falkordb.com/blog/vector-database-vs-graph-database/ This document explains the technical differences between vector databases and graph databases. It discusses how each type of database stores and mana
Quick review of a poll who asked attendees to identify their top priorities when developing machine learning based applications. The results show that the most important priority for the attendees was ensuring high accur
Ref: https://blogs.microsoft.com/blog/2024/10/21/new-autonomous-agents-scale-your-team-like-never-before/ Microsoft is announcing new autonomous agents that can be used to automate business processes. These agents are p
This article explores the benefits of using a knowledge graph database, FalkorDB, for building Retrieval-Augmented Generation (RAG) applications. RAG applications aim to enhance the capabilities of large language models
This article from FalkorDB explains how knowledge graph tools can enhance the reasoning capabilities of large language models (LLMs) by providing structured context from a knowledge base. It differentiates knowledge grap
Base on a blog post by Guy Korland, CEO and Co-Founder of FalkorDB, discussing the various ways in which data is stored in databases. He highlights three main database storage models: row-based, column-based, and network
The article compares and contrasts knowledge graphs and vector databases, both of which are used to store and retrieve data but differ in their methods and strengths. Knowledge graphs are structured representations of in
The article "Code Visualization: Benefits, Best Practices & Popular Tools" explores the concept of code visualization, which is the process of transforming code into visual representations of its structure and relationsh
This article provides an overview of advanced Retrieval-Augmented Generation (RAG) techniques used to improve the performance and accuracy of large language models (LLMs). It describes how to use techniques such as pre-r
This article from the FalkorDB blog focuses on the use of tensors and sparse matrices for efficiently representing and manipulating graph data within the FalkorDB database. The article highlights the power of GraphBLAS,
This article from the FalkorDB blog focuses on the use of tensors and sparse matrices for efficiently representing and manipulating graph data within the FalkorDB database. The article highlights the power of GraphBLAS,
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FalkorDB Podcast: Innovating at the Intersection of Graphs, AI, and Databases is hosted by FalkorDB. The show is categorised under technology and has published 16 episodes.
FalkorDB Podcast: Innovating at the Intersection of Graphs, AI, and Databases has published 16 episodes.
FalkorDB Podcast: Innovating at the Intersection of Graphs, AI, and Databases regularly covers technology. It sits in the technology category.
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Episodes of FalkorDB Podcast: Innovating at the Intersection of Graphs, AI, and Databases average 14 minutes. a focused format where a clear narrative arc and tight preparation matter most.
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