Category: Graph Databases

Feed: Neo4j Graph Database Platform. Author: David Penick. “There’s a risk that your fraud detection becomes anecdotal because you become accustomed to certain addresses or names. You risk emphasizing the small-time fraudsters instead of the clever ones. The clever ones are the ones that don’t usually get caught,” said Marius Hartmann, Chief Advisor, Danish Business Authority.The best time to stop a fraudulent business is at the very beginning, when the business registers with the government. That’s the role of the Danish Business Authority, where the team uses graph data science to predict fraud and stores detailed data about every decision ... Read More

Feed: Blog – ArangoDB. Author: Max Neunhöffer. Recently, we decided to investigate why our application ARANGOSYNC for synchronizing two ArangoDB clusters across data centers used up a lot of memory – around 2GB in certain cases. The environment contained ~1500 shards with 5000 GOroutines. Thanks to tools like pprof (to profile CPU and memory usage) it was very easy to identify the issue. The GO profiler showed us that memory was allocated in the function time.After() and it accumulated up to nearly 1GB. The memory was not released so it was clear that we had a memory leak. We will explain ... Read More

Feed: Neo4j Graph Database Platform. Author: Jocelyn Hoppa. Graph databases are the fastest growing database technology. Some people are drawn to graph databases for technical or performance reasons; others become interested because of the intuitive data model. One thing is clear: Graphs represent a departure from the relational and NoSQL models, but this departure is inherently worthwhile.Graph Databases For Dummies, Neo4j Special Edition is all about getting started with graph databases. We remember what it was like for us learning about Neo4j and graphs, and thought hard about the book we would have liked back then. With this book, we ... Read More

Feed: Cambridge Intelligence. Author: Dan Williams. We’re very excited to add KronoGraph, our timeline visualization toolkit, to our product line-up. It fills a huge hole in the market for people who want to build rich, interactive timelines into investigative applications. It also complements our market-leading graph visualization toolkits perfectly, giving you a brand new way to look at your connected data.In this blog we’ll take a look at five of the most common applications and use cases for timeline data analysis. The timeline images you see were built using KronoGraph, in some cases combined with KeyLines or ReGraph. 1: ... Read More

Feed: Neo4j Graph Database Platform. Author: Corin Gainey. Editor’s Note: This presentation was given by Craig Taverner at NODES 2019.Presentation SummaryCraig Taverner, Senior Software Engineer at Neo4j, presents Building Spatial Search Algorithms at Nodes 2019.Taverner briefly runs over some Neo4j history before presenting the two new data types debuted in Neo4 3.4: temporal and spatial. For the sake of this presentation, the focus will be on spatial data.In the Spring and Summer of 2019, Eindhoven University student Stephan van der Lind interned at the Neo4j office in Malmo and did some work on Spatial Algorithms.The task he was given was ... Read More

Feed: Neo4j Graph Database Platform. Author: David Penick. Money laundering is among the hardest activities to detect in the world of financial crime. Funds move in plain sight through standard financial instruments, transactions, intermediaries, legal entities and institutions – avoiding detection by banks and law enforcement. The costs in regulatory fines and damaged reputation for financial institutions are all too real. Neo4j provides an advanced, extensible foundation for fighting money laundering, reducing compliance costs and protecting brand value.In this final blog in our series, we look at how graph data visualizations help uncover money laundering and dig into Neo4j performance ... Read More

Feed: Neo4j Graph Database Platform. Author: Mark Needham. Hi graph gang, In this week’s video, Will Lyon shows us how to get started with Neo4j, Gatsby, and GraphQL. Max De Marzi shows how to solve a tricky problem using the Traversal API, Adam Cowley builds a Knowledge Graph from Slack archives, and M. David Allen published architecture documentation for Neo4j and Kafka And finally, Tomaz Bratanic does a deep dive into the path finding algorithms in the Graph Data Science Library. Cheers, Mark, Karin, and the Developer Relations team This week’s featured community member is Alexander Erdl. Alexander Erdl ... Read More

Feed: Neo4j Graph Database Platform. Author: Jocelyn Hoppa. I’m thrilled to have Charlie Beveridge with us for a 5-minute interview on the future of knowledge graphs. Charlie is a Senior Consulting Manager at Accenture and leads the company’s AI propositions for clients in the Telco and Media industries.Carlie works with client teams in both the front and back office spaces to help them take advantage of the things new technologies are enabling them to do. And, knowledge graphs are one of those technologies she’s seeing have the greatest impact for Accenture’s clients.Julia Astashkina: So, what is a knowledge graph?Charlie Beveridge: ... Read More

Feed: Neo4j Graph Database Platform. Author: Enzo. Editor’s Note: This presentation was given by Tim Ward at GraphConnect New York City in September 2018.Presentation SummaryTim Ward is the founder of CluedIn, helping companies bring together data scattered across the organization, become much more data-driven – and ultimately become connected enterprises.In this presentation, he will explain why an enterprise needs to be connected and then breaks down three steps your enterprise must go through to achieve that.The first step is integrating your data. Whether it’s in real time or not, data integration requires enterprise-level authentication that changes fast but not too ... Read More

Feed: Cambridge Intelligence. Author: Catherine Kearns. Cambridge Intelligence, creators of data visualization technologies that make the world safer, today announced KronoGraph: a new way to build scalable timeline visualizations.KronoGraph is the world’s first developer toolkit for building browser-based, interactive, investigative timeline visualizations that reveal how events unfold. It’ll revolutionize the way investigators understand their time-based data in use cases from security to anti-fraud, cyber security to IT infrastructure management and more. KronoGraph’s timeline visualizations make it easy to spot events that drive investigations.Tools built with KronoGraph give users fast, intuitive insight into sequences of events and how they ... Read More