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Neo4j

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DeepHub IMBA
DeepHub IMBA
Jun 25, 2026 · Artificial Intelligence

Transform a Single RAG Pipeline with LangGraph – Agent Picks Vector, Graph or Web Search

This article demonstrates how to use LangGraph to build a state‑machine‑based hybrid RAG agent that routes each query to the most suitable retriever—vector similarity, graph traversal, or web search—through a Router, and then validates answers with grading, rewriting, generation, and hallucination‑checking components.

Agentic RetrievalFAISSLLM
0 likes · 12 min read
Transform a Single RAG Pipeline with LangGraph – Agent Picks Vector, Graph or Web Search
Su San Talks Tech
Su San Talks Tech
Jun 7, 2026 · Databases

Master Neo4j: Complete Beginner’s Guide, Core Concepts, Cypher Commands, and Spring Boot Integration

This article introduces Neo4j, explains how graph databases differ from relational tables, walks through three installation methods, details nodes, relationships, and paths, provides extensive Cypher examples for creating, querying, updating, and deleting data, and shows how to integrate Neo4j with Spring Boot, plus pros, cons, and use cases.

CypherInstallationNeo4j
0 likes · 19 min read
Master Neo4j: Complete Beginner’s Guide, Core Concepts, Cypher Commands, and Spring Boot Integration
James' Growth Diary
James' Growth Diary
May 22, 2026 · Artificial Intelligence

Advanced Graph RAG with Neo4j: When Multi‑Hop Reasoning Beats Vector Search

This article explains why vector retrieval fails on multi‑hop reasoning, shows how Neo4j’s Cypher path traversal enables precise Graph RAG queries, outlines modeling best‑practices, demonstrates hybrid graph‑vector retrieval, compares Graph RAG with vector RAG, and lists common pitfalls to avoid.

CypherGraph RAGHybrid Retrieval
0 likes · 21 min read
Advanced Graph RAG with Neo4j: When Multi‑Hop Reasoning Beats Vector Search
James' Growth Diary
James' Growth Diary
May 21, 2026 · Databases

Building a Neo4j Knowledge Graph: Entity Modeling, Cypher Queries, and LangChain Integration

This article walks through why graph databases excel at multi‑hop queries, compares Neo4j with relational and vector stores, explains core concepts of nodes, relationships and properties, shows Docker setup, demonstrates six common Cypher patterns, integrates LangChain for LLM‑generated queries, and shares production‑grade modeling tips and pitfalls.

CypherKnowledge GraphLangChain
0 likes · 19 min read
Building a Neo4j Knowledge Graph: Entity Modeling, Cypher Queries, and LangChain Integration
James' Growth Diary
James' Growth Diary
May 12, 2026 · Artificial Intelligence

GraphRAG Deep Dive: Boost Multi‑Hop Reasoning Accuracy from 50% to 85% with Knowledge Graphs

This article explains why traditional vector RAG loses relational information, how GraphRAG reconstructs entity‑relationship triples into a knowledge graph, and provides step‑by‑step code, performance benchmarks, retrieval modes, and practical tips that raise multi‑hop reasoning accuracy from around 50% to 85%.

GraphRAGKnowledge GraphLangChain
0 likes · 14 min read
GraphRAG Deep Dive: Boost Multi‑Hop Reasoning Accuracy from 50% to 85% with Knowledge Graphs
The Dominant Programmer
The Dominant Programmer
Apr 29, 2026 · Databases

Getting Started with Spring Boot and Neo4j: Step‑by‑Step Guide and Sample Code

This article introduces Neo4j as a graph database, walks through its Windows installation, and provides a complete Spring Boot integration tutorial—including Maven dependencies, YAML configuration, entity and repository definitions, REST controller implementation, and end‑to‑end testing of user and follow‑relationship APIs.

Neo4jREST APISpring Boot
0 likes · 8 min read
Getting Started with Spring Boot and Neo4j: Step‑by‑Step Guide and Sample Code
Data STUDIO
Data STUDIO
Apr 2, 2026 · Artificial Intelligence

Building a Dual‑Stack Memory Agent: Situational + Semantic Memory for Long‑Term AI Understanding

This tutorial walks through designing and implementing a dual‑stack memory architecture for AI agents—combining episodic vector‑based situational memory with graph‑based semantic memory—using LangChain, FAISS, and Neo4j, and demonstrates a complete end‑to‑end workflow with code examples.

Agent MemoryFAISSKnowledge Graph
0 likes · 14 min read
Building a Dual‑Stack Memory Agent: Situational + Semantic Memory for Long‑Term AI Understanding
AI Architecture Hub
AI Architecture Hub
Dec 27, 2025 · Artificial Intelligence

How GraphRAG Turns Knowledge Graphs into Smarter Retrieval for LLMs

GraphRAG extends traditional Retrieval‑Augmented Generation by building a knowledge graph from documents, extracting entities and relationships, performing community detection, and supporting both local and global searches, offering detailed step‑by‑step guidance, code examples, configuration tips, and a comparison with classic RAG approaches.

GraphRAGKnowledge GraphLLM
0 likes · 28 min read
How GraphRAG Turns Knowledge Graphs into Smarter Retrieval for LLMs
Architect
Architect
Dec 25, 2025 · Artificial Intelligence

How GraphRAG Boosts Retrieval Accuracy with Knowledge Graphs – A Complete Guide

This article explains why traditional RAG suffers from hallucinations, introduces GraphRAG’s knowledge‑graph‑based approach, walks through its indexing and query pipelines—including text splitting, entity‑relation extraction, graph construction, community detection, and local vs. global retrieval—provides practical setup commands, Neo4j visualization steps, and compares its performance with classic RAG.

EmbeddingGraphRAGKnowledge Graph
0 likes · 27 min read
How GraphRAG Boosts Retrieval Accuracy with Knowledge Graphs – A Complete Guide
Data Party THU
Data Party THU
Aug 22, 2025 · Artificial Intelligence

How BAML Turns a 25% Success Rate into 99%+ for Knowledge‑Graph Extraction with Small LLMs

This article presents a systematic study of extracting knowledge graphs from unstructured news articles using small quantized LLMs, exposing the brittleness of LangChain's JSON‑based pipelines, evaluating prompt‑engineering fixes, and introducing the BAML framework whose fuzzy parsing and concise schema raise extraction success from roughly 25% to over 99% on a 344‑document benchmark.

BAMLGraphRAGLLM
0 likes · 33 min read
How BAML Turns a 25% Success Rate into 99%+ for Knowledge‑Graph Extraction with Small LLMs
Model Perspective
Model Perspective
Aug 4, 2025 · Databases

How to Build a Comprehensive Mathematical Modeling Knowledge Graph

This article explains why a mathematical modeling knowledge graph is needed, outlines its multi‑layer structure, and provides step‑by‑step guidance—from defining scope and collecting concepts to modeling nodes and relationships and visualizing the graph with Neo4j—highlighting its educational and research benefits.

AIKnowledge GraphNeo4j
0 likes · 8 min read
How to Build a Comprehensive Mathematical Modeling Knowledge Graph
Model Perspective
Model Perspective
Jul 25, 2025 · Databases

How to Model and Deploy Knowledge Graphs with Neo4j and Python

This article explains the fundamentals of knowledge graph representation, including entities, concepts, relationships, and triple structures, and provides step‑by‑step instructions for installing Neo4j, configuring Python with py2neo, and importing CSV‑based triples into a graph database for querying and reasoning.

Knowledge GraphNeo4jPython
0 likes · 12 min read
How to Model and Deploy Knowledge Graphs with Neo4j and Python
DaTaobao Tech
DaTaobao Tech
Sep 20, 2024 · Databases

Database Technology Evolution: From Hierarchical to Vector Databases

The article chronicles the evolution of database technology from early hierarchical and network models through relational, column‑store, document, key‑value, graph, time‑series, HTAP, and finally vector databases, detailing each system’s architecture, strengths, limitations, typical uses, and future trends toward specialization, distributed cloud‑native designs, and AI‑driven applications.

HBaseHTAPInfluxDB
0 likes · 52 min read
Database Technology Evolution: From Hierarchical to Vector Databases
AI Large Model Application Practice
AI Large Model Application Practice
Aug 16, 2024 · Artificial Intelligence

How to Query a Microsoft GraphRAG Knowledge Graph with Neo4j: Local and Global Modes

This guide explains how to query a Microsoft GraphRAG knowledge graph using the official CLI, API, and a custom Neo4j implementation, covering both local and global retrieval modes, vector index creation, Cypher query customization, and integration with LangChain for end‑to‑end RAG pipelines.

LangChainMicrosoft GraphRAGNeo4j
0 likes · 13 min read
How to Query a Microsoft GraphRAG Knowledge Graph with Neo4j: Local and Global Modes
AI Large Model Application Practice
AI Large Model Application Practice
Aug 9, 2024 · Artificial Intelligence

How to Build and Index Microsoft GraphRAG with Neo4j: A Step‑by‑Step Guide

This article explains the fundamentals of Microsoft GraphRAG, details its indexing pipeline—including text chunking, entity‑relationship extraction, community detection, and description generation—shows how to set up the graphrag library, create adaptive prompts, build the index, and import the resulting graph into Neo4j for visualization and analysis.

AIGraphRAGNeo4j
0 likes · 13 min read
How to Build and Index Microsoft GraphRAG with Neo4j: A Step‑by‑Step Guide
JD Tech
JD Tech
Jul 15, 2024 · Databases

A Comprehensive Overview of Nine Database Types and Polyglot Persistence Practices

This article provides an in‑depth survey of nine database categories—including relational, key‑value, columnar, document, graph, time‑series, and vector databases—detailing their architectures, advantages, disadvantages, best‑practice recommendations, typical use cases, and how they can be combined in polyglot persistence solutions.

ClickHouseDatabase TypesHBase
0 likes · 41 min read
A Comprehensive Overview of Nine Database Types and Polyglot Persistence Practices
JavaEdge
JavaEdge
Jul 13, 2024 · Databases

Mastering Neo4j: From Basics to Advanced Graph Queries and Performance Tuning

This article introduces Neo4j, explains its property‑graph model, demonstrates how to write and optimize Cypher queries, explores advanced features like full‑text search and built‑in graph algorithms, and showcases real‑world use cases and integration options for modern applications.

CypherFull-Text SearchGraph Queries
0 likes · 10 min read
Mastering Neo4j: From Basics to Advanced Graph Queries and Performance Tuning
Huolala Tech
Huolala Tech
Jan 16, 2024 · Information Security

How Graph Databases Revolutionize Host Security Incident Response

This article explores how HuoLala's host security HIDS leverages Neo4j graph databases and the Neovis.js visualization library to unify process, network, and file data, enabling rapid attack‑chain reconstruction, efficient multi‑cloud incident response, and improved security operations.

CypherHost SecurityNeo4j
0 likes · 16 min read
How Graph Databases Revolutionize Host Security Incident Response
DataFunTalk
DataFunTalk
Oct 15, 2023 · Artificial Intelligence

Building an Event Knowledge Graph for Telecom Network Operations

This article describes how China Telecom's AI R&D Center designs and implements a network operations event knowledge graph using AI techniques, graph databases, and UIE models to improve fault handling, automate recommendations, and enhance intelligent assistance for telecom network maintenance.

AIKnowledge GraphNeo4j
0 likes · 16 min read
Building an Event Knowledge Graph for Telecom Network Operations
DataFunTalk
DataFunTalk
Jan 14, 2023 · Databases

Evolution and Architecture of Graph Databases: From Early Designs to Modern Distributed Systems

This article surveys the development of graph databases, describing their underlying data models, storage designs across relational, native, document, and wide‑column systems, and reviewing representative modern distributed graph databases while discussing current challenges and future directions such as GQL standardization and graph‑AI integration.

NebulaGraphNeo4jNoSQL
0 likes · 29 min read
Evolution and Architecture of Graph Databases: From Early Designs to Modern Distributed Systems
DataFunTalk
DataFunTalk
Aug 24, 2022 · Databases

Building Intelligent Supply Chains with Graph Databases and Knowledge Graphs

This article explains how the data challenges of modern intelligent supply chains can be addressed by using graph databases and knowledge graphs, detailing supply chain background, graph database fundamentals, graph algorithms, and real‑world case studies that illustrate risk assessment and logistics optimization.

Knowledge GraphNeo4jgraph algorithms
0 likes · 18 min read
Building Intelligent Supply Chains with Graph Databases and Knowledge Graphs
DataFunTalk
DataFunTalk
Jul 13, 2022 · Databases

Technical Analysis and Case Studies of Knowledge Graphs by Neo4j

This presentation explains where knowledge resides in data architectures, demonstrates knowledge‑graph‑driven skill discovery, metadata management, and semantic search, and concludes with a comparison of GraphQL and Cypher for graph queries, illustrated with real‑world Neo4j case studies.

CypherGraphQLKnowledge Graph
0 likes · 11 min read
Technical Analysis and Case Studies of Knowledge Graphs by Neo4j
Aikesheng Open Source Community
Aikesheng Open Source Community
Jan 19, 2022 · Databases

Using Neo4j to Complement MySQL for Complex Relationship Queries

The article demonstrates how MySQL handles simple relationship queries efficiently but struggles with deep relational traversals, and shows how the graph database Neo4j can replace MySQL in such scenarios, providing faster query execution and better scalability for multi‑level social connections.

Neo4jRelationship Queriesgraph database
0 likes · 10 min read
Using Neo4j to Complement MySQL for Complex Relationship Queries
vivo Internet Technology
vivo Internet Technology
Oct 13, 2021 · Databases

Understanding Graph Databases: Concepts, Trends, and Neo4j Example

The article explains graph databases—where nodes and edges model entities and relationships—covers their query languages, rapid global popularity since 2014, Neo4j’s property‑graph implementation and example knowledge graph, compares alternatives, and urges Chinese researchers to pursue independent theoretical and engineering innovation.

Database TrendsIndependent InnovationKnowledge Graph
0 likes · 6 min read
Understanding Graph Databases: Concepts, Trends, and Neo4j Example
IT Architects Alliance
IT Architects Alliance
Aug 31, 2021 · Databases

Why Graph Databases Matter: From Basics to Neo4j vs JanusGraph

The article explains the rapid rise of graph databases, outlines their core concepts and advantages, compares them with NoSQL and relational databases, presents performance benchmarks, and reviews leading solutions such as Neo4j and JanusGraph, including their data models and query language.

CypherJanusGraphNeo4j
0 likes · 10 min read
Why Graph Databases Matter: From Basics to Neo4j vs JanusGraph
ITPUB
ITPUB
Aug 30, 2021 · Databases

Why Graph Databases Are Revolutionizing Data Relationships: Neo4j vs JanusGraph

This article explains the rise of graph databases, compares them with traditional relational and NoSQL systems, details the differences between Neo4j and JanusGraph, and demonstrates how the Cypher query language enables efficient relationship queries in complex, large‑scale data environments.

CypherJanusGraphNeo4j
0 likes · 12 min read
Why Graph Databases Are Revolutionizing Data Relationships: Neo4j vs JanusGraph
Python Programming Learning Circle
Python Programming Learning Circle
Dec 5, 2020 · Databases

Using Neo4j Graph Database with Py2neo: Nodes, Relationships, Subgraphs, Walkable, and OGM

This article provides a comprehensive guide to Neo4j, an open‑source graph database, covering its data model, key features, installation, and detailed Python usage with the Py2neo library, including node and relationship creation, property handling, subgraph operations, walkable traversals, and object‑graph mapping (OGM).

CQLNeo4jOGM
0 likes · 16 min read
Using Neo4j Graph Database with Py2neo: Nodes, Relationships, Subgraphs, Walkable, and OGM
Programmer DD
Programmer DD
Nov 1, 2020 · Backend Development

What’s New in Spring Data Ockham (2020.0.0) Release?

The October 2020 Spring Data Ockham (2020.0.0) release introduces a new version‑naming scheme, updates to Spring Data Neo4j, JDBC, R2DBC, Redis, adds RxJava 3 and De‑lombok support, and outlines compatibility notes for Spring Boot 2.4 and Neo4j users.

Backend DevelopmentJavaNeo4j
0 likes · 3 min read
What’s New in Spring Data Ockham (2020.0.0) Release?
Architects Research Society
Architects Research Society
Aug 17, 2020 · Databases

Interview with JanusGraph PMC Members on Graph Database Landscape, Neo4j Comparison, and Deployment Best Practices

In this interview, JanusGraph PMC members Florian Hockmann and Jason Plurad discuss the project's origins, compare JanusGraph with Neo4j, share advice for production deployments, outline future expectations for JanusGraph and TinkerPop, and provide practical tips for graph modeling and community contribution.

CassandraElasticsearchGremlin
0 likes · 16 min read
Interview with JanusGraph PMC Members on Graph Database Landscape, Neo4j Comparison, and Deployment Best Practices
Architecture Digest
Architecture Digest
May 9, 2020 · Databases

Understanding Graph Databases: Concepts, Comparisons, and Query Language

This article introduces graph databases, explains their underlying graph model, compares them with NoSQL and relational databases, reviews popular implementations such as Neo4j and JanusGraph, and demonstrates querying with the Cypher language, highlighting their advantages for complex relationship queries in modern data‑intensive applications.

CypherJanusGraphNeo4j
0 likes · 10 min read
Understanding Graph Databases: Concepts, Comparisons, and Query Language
37 Interactive Technology Team
37 Interactive Technology Team
Feb 20, 2020 · Artificial Intelligence

Risk Control System for Detecting Game Account Fraud Using Feature Engineering and Graph Database

The article describes a risk‑control pipeline for detecting high‑volume fraudulent game accounts, detailing data collection from game logs, extensive feature engineering and statistical tests, enrichment via a Neo4j knowledge graph, and a hybrid RandomForest‑GBDT model combined with methods to filter personal accounts.

Neo4jdata miningfeature engineering
0 likes · 8 min read
Risk Control System for Detecting Game Account Fraud Using Feature Engineering and Graph Database
Qunar Tech Salon
Qunar Tech Salon
Aug 29, 2019 · Information Security

Using Graph Databases for Fraud Detection in Ride‑Hailing Platforms

The article explains how building a Neo4j‑based social graph of users, drivers, devices and other attributes enables detection of individual and group subsidy‑abuse fraud in ride‑hailing services through multi‑hop relationship analysis and targeted rule‑based alerts.

Neo4jRide HailingSocial Network Analysis
0 likes · 6 min read
Using Graph Databases for Fraud Detection in Ride‑Hailing Platforms
21CTO
21CTO
Feb 12, 2019 · Databases

From MariaDB CTO to Neo4j: Ivan Zoratti’s Journey into Graph Databases

Former MariaDB CTO Ivan Zoratti shares his 35‑year tech career, the evolution from MySQL to MariaDB, why he transitioned to Neo4j, and his insights on graph versus relational databases, highlighting the innovations and future potential of graph technology.

MariaDBNeo4jRelational Databases
0 likes · 12 min read
From MariaDB CTO to Neo4j: Ivan Zoratti’s Journey into Graph Databases
ITPUB
ITPUB
Jan 10, 2019 · Databases

Mastering Neo4j: From Graph Modeling to Advanced Cypher Queries

This comprehensive guide explains Neo4j's label‑property graph model, node and relationship creation, Cypher syntax, indexing, constraints, schema inspection, and best practices for avoiding duplicate data, providing practical examples and performance tips.

ConstraintsCypherIndexing
0 likes · 29 min read
Mastering Neo4j: From Graph Modeling to Advanced Cypher Queries
21CTO
21CTO
Mar 25, 2018 · Databases

Choosing Between Neo4j and OrientDB: A Practical Guide to Building Knowledge Graphs

This article explains the origins of knowledge graphs, introduces the leading graph databases Neo4j and OrientDB, demonstrates their Java client usage, and compares their features to help developers select the most suitable technology for constructing effective knowledge graph solutions.

CypherJavaKnowledge Graph
0 likes · 12 min read
Choosing Between Neo4j and OrientDB: A Practical Guide to Building Knowledge Graphs
Java Backend Technology
Java Backend Technology
Jan 17, 2018 · Databases

Why Graph Databases Outperform Relational DBs for Social Network Queries

The article explains the limitations of relational databases for large‑scale, highly connected data, introduces NoSQL and graph database models, demonstrates how graph queries efficiently retrieve multi‑degree social connections, and showcases Neo4j’s performance advantages over traditional RDBMS.

Database PerformanceNeo4jNoSQL
0 likes · 14 min read
Why Graph Databases Outperform Relational DBs for Social Network Queries