Today, Amazon Web Services (AWS) announced the general availability of Amazon Bedrock Knowledge Bases GraphRAG (GraphRAG), a capability in Amazon Bedrock Knowledge Bases that enhances Retrieval-Augmented Generation (RAG) with graph data in Amazon Neptune Analytics. In this post, we discuss the benefits of GraphRAG and how to get started with it in Amazon Bedrock Knowledge Bases.

Integrating Neo4j, DuckDB, and Kestra for Metadata-Driven Graph Design

An open-source Python framework for real-time, graph-based knowledge in Neo4j

We’re thrilled to announce new Text2Cypher models and Google’s MCP Toolbox for Databases from the collaboration between Google Cloud and Neo4j.

The Model Context Protocol gives users a wide range of services they can connect to from the comfort of their AI client.

Learn how to use Spanner Graph with LangChain workflows to build advanced, relationship-aware RAG systems, a.k.a. GraphRAG.

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Build a graph for RAG application for a price of a chocolate bar! What is GraphRAG for you? What is GraphRAG? What does GraphRAG mean from your perspective? What if you could have a standard RAG and a GraphRAG as a combi-package, with just a query switch? The fact is, there is no concrete, universal

Bridge the gap and unlock hidden potential within your unstructured data

New features include community summaries, local and global retrievers, running retrievers in parallel, and custom prompt instructions.

When (not) to use GraphRAG

Explore its functionality and how it leverages the power of LLMs and Neo4j graph databases to improve data analysis and knowledge discovery.

Enabling an LLM to chat directly with structured graph data

Today, I conducted a comparison between ChatGPT and DeepSeek chat capabilities by providing them with a schema and a natural language question. I tasked them…

David Hughes presented “Unleashing the Power of Multimodal GraphRAG: Integrating Image Features for Deeper Insights” at Data Day Texas 2025.

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As technology advances, large language models (LLMs) and information retrieval/management methods evolve at breakneck speed. Knowledge…

A RAG System Built for Both Semantic Search and Structured Data Queries

Authors: Makbule Gulcin Ozsoy, Leila Messallem, Jon Besga

Authors: Makbule Gulcin Ozsoy, Leila Messallem, Jon Besga

A deep dive into LangChain’s implementation of graph construction with LLMs

Using SPARQL and the Knowledge Graph for RAG

Many people have asked about loading Microsoft Research #GraphRAG data into Neo4j. I wrote a quick notebook last night to import Documents, Chunks (TextUnit)… | 27 comments on LinkedIn

End to end solution for migrating CSV data into a Neo4j graph using an LLM for the data discovery and graph data modeling stages. - a-s-g93/neo4j-runway

This notebook converts CSV data into a Neo4j Graph Database. All you do is describe your data. Have you wanted to see what your data looked like as a graph…

When to use graph data models, such as parent-child, question-based, and topic-summary, for RAG applications powered by knowledge graphs.

Optimizing vector retrieval with advanced graph-based metadata techniques using LangChain and Neo4j Editor's Note: the following is a guest blog post from Tomaz Bratanic, who focuses on Graph ML and GenAI research at Neo4j. Neo4j is a graph database and analytics company which helps organizations find hidden relationships and patterns