In this episode of Graph Geeks in Discussion, host Amy Hodler sits down with Arthur Bigeard, founder of G.V(), to explore how his quest for a user-friendly graph database client led to creating a more universal graph experience tool. Arthur shares his journey from graph database novice to tool creator, explaining how G.V() bridges the gap between technical complexity and practical usability across multiple graph database technologies.

G.V() website: https://gdotv.com/

KGC Conference referenced: https://events.knowledgegraph.tech/

This podcast episode features host Amy Hodler in conversation with Joe Eaton, NVIDIA Distinguished System Engineer, discussing graph analytics acceleration technologies. This discussion covered:

• How RAPIDS and cuGraph are changing graph analytics through GPU acceleration
• Their innovative approach to scaling NetworkX on GPUs without requiring code modifications
• An exploration of GNNs, graph embeddings, and vector search applications

We also looked at current trends in graph technology and their real-world implications. Joe provided pointers to resources (below) for people just getting started as well as his picks for exciting graph-related talk at the upcoming NVIDIA GTC conference.

Getting Started with RAPIDS and cuGraph

https://rapids.ai/

Graph Talks at GTC

https://nvda.ws/4bofZ4e

In this fun episode of GraphGeeks in Discussion, host Amy Hodler sits down with William Lyon, who is currently heading developer experience at Hypermode and a respected figure in the graph database community. Drawing from his rich experience at Neo4j and Dgraph, Will offers unique insights into the evolving landscape of graph technologies.

As a veteran in the graph space, Will shares his personal journey through different graph database architectures and insights on using property graphs and triples for data management.

Additional information:

https://dgraph.io/ https://hypermode.com/ https://github.com/hypermodeinc/modus Recipes on https://github.com/hypermodeinc/modus-recipes

The "the Kleinberg Book" mentioned on Networks, Crowds, and Markets: https://www.cs.cornell.edu/home/kleinber/networks-book/

Today's conversation with Claudia Natasia, CEO of Riley, takes us into the fascinating intersection of graph technology and customer behavior. As a data scientist turned product leader, Claudia discovered that the key to unlocking revenue growth was hidden in the complex web of customer data. That insight led her to found a company that's revolutionizing how businesses understand their customers using the power of graph technology. Join us as we explore her journey from data-driven problem solver to innovative tech founder, and learn how companies are uncovering elusive customer insights.

Listen to Amy Hodler interview Jesse Kallman, Founder & CEO at Danti, and Anthony Hylick, their Head of Machine Learning. Learn why Earth-Data is increasingly important today and how Danti uses graphs and AI to power its search engine. https://danti.ai/

Hear how this context-rich search goes beyond geospatial to enable users—from government agencies to private enterprises—to find the precise data they need from the vast, ever-growing datasets collected by satellites, drones, and other sources around the globe.

Listen to this GraphGeeks podcast to learn about Streaming Graphs for Cybersecurity. Our graph practitioners will appreciate hearing about graph event stream processing, and our cybersecurity listeners will learn how graphs are used to detect complex patterns and advanced persistent threats. 

Our guests include Paige Roberts, who’s had various roles in her 25 years in software and is currently the Director of Product Innovation for thatDot. Paige has also co-authored and contributed to several O’Reilly books, including “97 Things Every Data Engineer Should Know” and “Accelerate Machine Learning with a Unified Analytics Architecture.”

We also have our cybersecurity expert, John Cloonan, who has 25 years of experience deploying security controls, combating network attacks, and bringing new cyber solutions to market. John is now the VP of Product at thatDot.

Resources discussed on this podcast:

• Open source streaming graph quine.io/ 
• The blog on scaling - www.thatdot.com/resource-post/scaling-quine-streaming-graph-to-process-1-million-events-second/
• The SANS Institute for Cybersecurity Training and Certification - www.sans.org/  

Listen to Amy Hodler interview Semih Salihoğlu, CEO of Kuzu and professor at the University of Waterloo, to learn about the fascinating history of graphs through the lens of database management systems. In this podcast, Semih walks us through the evolution of systems: from the first database system, IDS, to modern property graph databases, such as Neo4j and Kùzu. 

You’ll learn about the connections between the birth of the World Wide Web and document-based datasets and document stores, such as MongoDB. Amy and Semish also discuss the flexibility of RDF as a reasoning system and ties to the semantic web.

In this quick history of graph databases, you’ll discover the roots of features that we see in modern graph database management systems and gain an appreciation for the collective innovations. 

Semih Salihoğlu Video Series https://www.youtube.com/@KuzuDB

Further Reading on the Early History https://tomandmaria.com/Tom/Writing/VeritableBucketOfFactsSIGMOD.pdf 

2002 Interview with Charlie Bachman https://www.youtube.com/watch?v=iDVsNqFEkB0

In this podcast, we discuss current trends in knowledge graphs with François Scharffe, the CEO of The Data Chefs and co-founder of The Knowledge Graph Conference (KGC). First, François gives us insights into the evolution of KGC and the popularity of using knowledge graphs for RAG (retrieval-augmented generation). Then, we dive into the early indications that knowledge graphs may help bring back rule-/expert-based systems and the possibilities around personal knowledge graphs.

https://www.thedatachefs.com/

https://www.knowledgegraph.tech/

Graphs are changing how we model, store, and query complex data. But when it comes to choosing the right type of graph model, the decision often boils down to two major contenders: Resource Description Framework (RDF) and Labelled Property Graphs (LPG). Each has its own unique strengths, use cases, and challenges.

Join this GraphGeeks talk with experts Jesús Barrasa and Dave Bechberger to better understand these approaches.

Sneak peek of Maya Natarajan's talk at KGC on graph market.