#GraphCast: Graph Analytics For The Throne [GoT]

Welcome to this week’s #GraphCast – our series featuring what you might have missed in Neo4j media from the past fortnight. Last time, I pointed out that we have an incredible Neo4j Online Meetup and that you’re a square if… Read more →

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Announcing Neo4j Labs: Incubating the Next Generation of Graph Developer Tooling

As the Director of the Developer Relations engineering team, I couldn’t be more proud of the things we have achieved over the last few years. Our focus was to build integrations, tools and libraries that extend the Neo4j Graph Platform… Read more →

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Graph Algorithms in Neo4j: Louvain Modularity

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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This Week in Neo4j – Neo4j Joins GraphQL Foundation as a Founding Member, Desktop Graph Analytics, Revamped Intro to Neo4j Training Course

This Neo4j community has had another busy week. We launched a revamped Intro to Neo4j online course, available for the bargain price of $0. Irfan Karaca and I had fun showing off Neuler – a Graph App that lets you… Read more →

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Graph Algorithms in Neo4j: Label Propagation

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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This Week in Neo4j – Correlating Tags in Stackoverflow, Football meets graphs, All About the Kafka Connect Neo4j Sink Plugin

This week Bea Hernández shared the slides from her talk at SatRDays on my favourite two topics – football and graphs! The Kafka connector that we’ve previously featured was released in the Confluent Marketplace, and Michael Hunger showed us how… Read more →

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Graph Algorithms in Neo4j: Weakly Connected Components

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: Strongly Connected Components

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Apache Spark Developers Have Voted to Include Cypher in Spark 3.0 [Update]

The community vote by Apache Spark contributors has just closed – and the results are positive. Thank you to everyone who participated when we asked for your votes and feedback. As part of the preparations for a forthcoming Apache Spark… Read more →

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Graph Algorithms in Neo4j: Closeness Centrality

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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DeepWalk: 5-Minute Interview with Dr. Steven Skiena

“Graphs have become very powerful, they’re fundamental, and they’re only becoming more and more important,” said Dr. Steven Skiena, Director of the AI Institute at Stony Brook University. Graphs are a fundamental part of computer science, and they are only… Read more →

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Graph Algorithms in Neo4j: Betweenness Centrality

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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This Week in Neo4j – Build a just-in-time data warehouse with Neo4j Streams, Releases of Graph Algorithms and Neo4j Desktop, Stored Procedure Masterclass

Welcome to the I can’t believe it’s already February edition of This Week in Neo4j. This week we have five (FIVE!) releases of different projects in the ecosystem, including the Neo4j Desktop, Graph Algorithms Library, and a brand new Python… Read more →

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Graph Algorithms in Neo4j: Degree Centrality

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: PageRank

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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This Week in Neo4j – Topic Extraction with Graphileon, Neo4j 3.5 FTS Deep Dive, Neo4j for Very Large Scale Systems

Welcome to the 3rd edition of This Week in Neo4j for 2019. We’ve got a variety of different things for you this week. Christophe Willemsen has written an excellent deep dive into the Full-Text Search feature released in Neo4j 3.5,… Read more →

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Apache Spark + Cypher: We Need Your Feedback & Votes

Editor’s Note: Alastair Green (Neo4j Query Languages Lead) and Martin Junghanns (Neo4j Cypher for Apache Spark project) will be speaking at the Spark + AI Summit in San Francisco this April. Want to Extend the Graph Capabilities of Spark? Let’s… Read more →

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A Journey to the Graph Side: How (& Why) the Former CTO of MariaDB Joined Neo4j [Interview]

If you don’t know anything about MariaDB – and you’re reading a database blog remember – then you’re the exception. In 2018, MariaDB was the second-fastest-growing relational database (behind Postgres) and is a leading example of commercially supported open source… Read more →

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Graph Algorithms in Neo4j: Minimum Weight Spanning Tree

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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This Week in Neo4j – Graph Layouts with Graph Algorithms and Machine Learning, Graphing the Floodlight Open Project data, Multi-Turn Conversational Voice Experiences with a Knowledge Graph

We’re almost half-way through January, so it must be time for another installment of This Week in Neo4j. It’s been a busy week as the community kicks back into action after the New Year’s hangover. Jennifer Reif is back with… Read more →

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Graph Algorithms in Neo4j: All Pairs Shortest Path

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: Single Source Shortest Path

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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This Week in Neo4j – Crime Investigation Sandbox, GraphQL to Cypher transpiler for the JVM, Exploring Yelp with Graph Algorithms

Welcome to This Week in Neo4j where I share the most interesting things I found in our community over the last seven days. This week Will and I previewed the Applied Graph Algorithms training, Joe Depeau launched the Crime Investigation… Read more →

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Graph Algorithms in Neo4j: Shortest Path

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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#GraphCast: Graph Algorithms & Game of Thrones

Welcome to this week’s #GraphCast – our new series featuring what you might have missed on the Neo4j YouTube channel. Last week, our Editor-in-Chief, Bryce Merkl Sasaki, shined some light back on our Intro to APOC video series (by Michael… Read more →

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