Graphs

July 9, 2026

From Knowledge Graphs to Context Graphs: The Next Evolution for AI Agents

How context graphs extend knowledge graphs with temporal validity, policy nodes, and decision traces — and why Gartner predicts 50% of enterprise AI agent systems will use them by 2028.

knowledge-graphscontext-graphsai-agentsmcp+2 more

July 9, 2026

GraphRAG Variants Compared in 2026

A systematic comparison of six GraphRAG variants in 2026 — Deep GraphRAG, CatRAG, ParallaxRAG, TagRAG, LeanRAG, and how GraphRAG-Bench measures them against vanilla RAG.

graphragdeep-graphragcatragparallaxrag+3 more

July 8, 2026

Graph-Powered OSINT: Why Knowledge Graphs Are the Missing Layer in Open Source Intelligence

Open Source Intelligence generates more data than any analyst can process. Knowledge graphs — not document silos — are the architecture that makes OSINT scalable, searchable, and analytically tractable.

osintknowledge-graphsneo4jgraph-theory+3 more

June 25, 2026

The Context Layer Race: Why Knowledge Graphs Are Becoming the Brain of Enterprise AI

AWS Context, Neo4j Document Intelligence, Databricks Genie Ontology, and FlureeDB all launched within weeks of each other. The message is clear: vector search alone isn't enough — AI agents need knowledge graphs to reason at scale.

knowledge-graphsai-agentscontext-layergraphrag+1 more

June 11, 2026

Knowledge Graphs for Vulnerability Prioritisation: Surviving the AI Patch Tsunami

Microsoft's record 206-CVE Patch Tuesday proves CVSS scores alone cannot prioritise. Knowledge graphs mapping dependency blast radius and reachability are the only scalable defence.

knowledge-graphssecurityvulnerabilitydependency-graph+3 more

June 10, 2026

GraphRAG at Mythos Scale: What Claude Fable 5 Means for Knowledge Graphs

Claude Fable 5's Mythos-class reasoning transforms GraphRAG from promising to production-ready. Multi-hop graph queries, reliable Text-to-Cypher, and autonomous graph exploration are now practical reality.

graphragclaudeknowledge-graphsllm-reasoning+1 more

June 10, 2026

Knowledge Graphs Are the Antidote to AI Hallucination Liability

After the Munich ruling made Google liable for false AI Overviews, GraphRAG offers the only legally defensible path for enterprise AI.

knowledge-graphsgraphragai-liabilityhallucination+1 more

June 9, 2026

Graph Theory 101: From First Principles

Graph theory from the ground up — vertices, edges, directed vs undirected, adjacency, degrees, paths, cycles, connectivity, and the fundamental theorems that power every graph database and algorithm.

graph-theorymathematicsdata-structuresalgorithms+1 more

June 8, 2026

The GQL Expressiveness Gap: What the New ISO Standard Can't Do

A technical deep dive into GQL's (ISO 39075) formal expressiveness limitations — including queries that recursive SQL can express but GQL cannot — with practical implications for database architects.

gqlcyphersqlgraph-database+4 more

June 8, 2026

GraphRAG Reality Check: When It Fails, Why, and How to Fix It

Evidence-based analysis of GraphRAG's failure modes — benchmarks where it underperforms vanilla RAG — with concrete mitigations and scenarios where graph-based retrieval dominates.

graphragragbenchmarkllm+3 more

June 8, 2026

GraphRAG for $30: Lazy Extraction That Actually Works

How LazyGraphRAG collapses GraphRAG indexing costs from $30,000 to $30 by deferring entity extraction to query time — with a practical guide to when lazy beats eager.

graphragragcost-optimizationllm+4 more

June 7, 2026

Ontology in Graph Databases: Lessons from Building a Medical Diagnostics Knowledge Graph

How a production Neo4j knowledge graph for medical diagnostics market intelligence implements ontology — node labels, edge semantics, signal normalisation, and what senior engineers can learn from 15 source adapters.

neo4jknowledge-graphsgraph-databasesontology+1 more

June 6, 2026

Neo4j Database Adapters Compared: Official and Community Drivers Across Every Major Language

A comprehensive comparison of Neo4j's official drivers (Python, JavaScript, Java, Go, .NET) and community adapters (Rust, PHP, Ruby, Elixir, Perl), with code examples, protocol support, and a decision matrix for choosing the right driver for your stack.

neo4jgraph-databasebolt-protocoldatabase-drivers+1 more

June 4, 2026

Graph Theory for Software Engineers: Practical Concepts

Essential graph theory concepts every software engineer should know — from traversal algorithms to centrality metrics — with real-world code examples.

graph-theoryalgorithmsdata-structuresbfs+2 more

June 4, 2026

Graph Visualization with Sigma.js: Building Interactive Network Views

A practical guide to building interactive graph visualizations using Sigma.js and Graphology — from basic setup to force-directed layouts.

sigma-jsgraphologyvisualizationjavascript+2 more

June 4, 2026

Introduction to GraphRAG: Combining Knowledge Graphs with RAG

GraphRAG enhances retrieval-augmented generation by grounding LLM responses in structured knowledge graphs instead of flat vector embeddings.

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June 4, 2026

Neo4j + AI: Building Intelligent Applications with Knowledge Graphs

Build AI-powered applications with Neo4j as the knowledge layer — from graph-backed RAG to autonomous graph agents.

neo4jknowledge-graphsgraphragllm+2 more

June 4, 2026

What Are Knowledge Graphs? A Practical Introduction

Understand knowledge graphs from first principles — RDF, property graphs, SPARQL, Cypher, and why they matter for AI applications.

knowledge-graphsrdfsparqlproperty-graph+1 more

Graphs

Graphs

Topics

Featured Content

All Graph Articles

From Knowledge Graphs to Context Graphs: The Next Evolution for AI Agents

GraphRAG Variants Compared in 2026

Graph-Powered OSINT: Why Knowledge Graphs Are the Missing Layer in Open Source Intelligence

The Context Layer Race: Why Knowledge Graphs Are Becoming the Brain of Enterprise AI

Knowledge Graphs for Vulnerability Prioritisation: Surviving the AI Patch Tsunami

GraphRAG at Mythos Scale: What Claude Fable 5 Means for Knowledge Graphs

Knowledge Graphs Are the Antidote to AI Hallucination Liability

Graph Theory 101: From First Principles

The GQL Expressiveness Gap: What the New ISO Standard Can't Do

GraphRAG Reality Check: When It Fails, Why, and How to Fix It

GraphRAG for $30: Lazy Extraction That Actually Works

Ontology in Graph Databases: Lessons from Building a Medical Diagnostics Knowledge Graph

Neo4j Database Adapters Compared: Official and Community Drivers Across Every Major Language

Graph Theory for Software Engineers: Practical Concepts

Graph Visualization with Sigma.js: Building Interactive Network Views

Introduction to GraphRAG: Combining Knowledge Graphs with RAG

Neo4j + AI: Building Intelligent Applications with Knowledge Graphs

What Are Knowledge Graphs? A Practical Introduction

Graphs

Graphs

Topics

Featured Content

All Graph Articles

From Knowledge Graphs to Context Graphs: The Next Evolution for AI Agents

GraphRAG Variants Compared in 2026

Graph-Powered OSINT: Why Knowledge Graphs Are the Missing Layer in Open Source Intelligence

The Context Layer Race: Why Knowledge Graphs Are Becoming the Brain of Enterprise AI

Knowledge Graphs for Vulnerability Prioritisation: Surviving the AI Patch Tsunami

GraphRAG at Mythos Scale: What Claude Fable 5 Means for Knowledge Graphs

Knowledge Graphs Are the Antidote to AI Hallucination Liability

Graph Theory 101: From First Principles

The GQL Expressiveness Gap: What the New ISO Standard Can't Do

GraphRAG Reality Check: When It Fails, Why, and How to Fix It

GraphRAG for $30: Lazy Extraction That Actually Works

Ontology in Graph Databases: Lessons from Building a Medical Diagnostics Knowledge Graph

Neo4j Database Adapters Compared: Official and Community Drivers Across Every Major Language

Graph Theory for Software Engineers: Practical Concepts

Graph Visualization with Sigma.js: Building Interactive Network Views

Introduction to GraphRAG: Combining Knowledge Graphs with RAG

Neo4j + AI: Building Intelligent Applications with Knowledge Graphs

What Are Knowledge Graphs? A Practical Introduction