Implementing graph RAG using knowledge graphs by LLcolD

Graph retrieval augmented generation (Graph RAG) is emerging as a powerful technique for generative AI applications to use domain-specific knowledge and relevant information. Graph RAG is an alternative to vector search methods that use a vector database. Knowledge graphs are knowledge systems where graph databases such as Neo4j or Amazon Neptune can represent structured data.

ByHackTechFebruary 20, 20250Comments

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Unraveling Graph Structures: Exploring Adjacency Matrices by ganderzz

Part of the From Nodes to Connections series.In Postgres: The Graph Database You Didn’t Know You Had we covered how we can store a DAG (Directed Acyclic Graph) in a relational database. We looked at one representation of a graph data structure called an adjacency list—a table with two columns representing how nodes connect. The

ByHackTechJuly 20, 20230Comments

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Kùzu 0.0.4 (Graph DB) by sdht0

Star Join Follow We are very happy to release Kùzu 0.0.4 today! This release comes with the following new main features and improvements: Kùzu 0.0.4 Release Data Ingestion Improvements New Cypher Features Undirected Relationships in Queries Recursive Queries: Shortest Path Queries and Improved Variable-length Queries New Data Types SERIAL STRUCT Client APIs

ByHackTechJune 5, 20230Comments

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High-Performance Graph Databases, Scaling to Hundreds of Thousands of Cores by belter

[Submitted on 18 May 2023] Authors:Maciej Besta, Robert Gerstenberger, Marc Fischer, Michał Podstawski, Jürgen Müller, Nils Blach, Berke Egeli, George Mitenkov, Wojciech Chlapek, Marek Michalewicz, Torsten Hoefler Download PDF Abstract: Graph databases (GDBs) are crucial in academic and industry applications. The key challenges in developing GDBs are achieving high performance, scalability, programmability, and portability. To

ByHackTechMay 21, 20231Comment

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Why Graph Databases Need New Join Algorithms: Story of Worst-Case Optimal Joins by semihsalihoglu

View it on GitHub Join our Slack workspace by Semih Salihoğlu, Feb 22nd, 2023 Joins of a sets of records is objectively the most expensive operation in DBMSs. In my previous post on factorization, I said that in the field of databases, once in a while you run into a very simple idea that deviates

ByHackTechFebruary 24, 20230Comments

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Once and for all: the promise of graph computing by yadongli

Every once in a while, there comes a technology so revolutionary that it changes the way people work and live. Blockchain, deep learning and cloud computing are examples of such. If you are searching for the next big thing, graph computing could be the answer.Why? Because graph computing solves the most common and costly problems…

ByHackTechMarch 9, 20220Comments

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Graph Database for Python by arun1729

Documents and examples at cogdb.io New release!: 3.0.1 Ability to use lambda in graph queries. Adjustable height and width for views. Installing Cog CogDB is a persistent graph database implemented purely in Python. Torque is CogDB’s graph query language. CogDB is an ideal choice if you need a database that is very easy to use…

ByHackTechJanuary 8, 20220Comments

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