Jim Webber Picture

Jim Webber

Chief Scientist, Neo4j

Jim Webber is the Chief Scientist at Neo4j working on next-generation solutions for massively scaling graph data. Prior to joining Neo4j, Jim was a Professional Services Director with ThoughtWorks where he worked on large-scale computing systems in finance and telecoms. Jim has a Ph.D. in Computing Science from the Newcastle University, UK.


Latest Posts by Jim Webber


Top 10 Use Cases: Identity and Access Management

Graph technology is the future. Not only do graph databases effectively store relationships between data points, but they’re also flexible in adding new kinds of relationships or adapting a data model to new business requirements. But how do companies today use graph databases to solve tough... read more



Top 10 Use Cases: Master Data Management

Graph technology is the future. Not only do graph databases effectively store relationships between data points, but they’re also flexible in adding new kinds of relationships or adapting a data model to new business requirements. But how do companies today use graph databases to solve tough... read more


Top 10 Use Cases: Empowering Network and IT Operations Management

Graph technology is the future. Not only do graph databases effectively store relationships between data points, but they’re also flexible in adding new kinds of relationships or adapting a data model to new business requirements. But how do companies today use graph databases to solve tough... read more


Discover how graph technology enhances artificial intelligence and machine learning with graph theory and algorithms.

Graphs for Artificial Intelligence and Machine Learning

Editor’s Note: This presentation was given by Dr. Jim Webber at GraphTour Boston in 2019. Full Presentation If there’s any area of computer science that’s prone to nonsense today, it’s artificial intelligence. I'm going to walk you through some no-nonsense definitions of AI-cronyms,... read more




Top 10 Use Cases: Knowledge Graphs

Graph technology is the future. Not only do graph databases effectively store relationships between data points, but they’re also flexible in adding new kinds of relationships or adapting a data model to new business requirements. But how do companies today use graph databases to solve tough... read more



Top 10 Graph Database Use Cases: Fraud Detection

Graph technology is the future. Not only do graph databases effectively store relationships between data points, but they’re also flexible in adding new kinds of relationships or adapting a data model to new business requirements. But how do companies today use graph databases to solve tough... read more


Learn everything you need to know about Neo4j 4.0 graph database.

Introducing Neo4j Graph Database 4.0 [GA Release]

I feel particularly pleased to be able to announce the GA release of Neo4j Graph Database 4.0. I've been with the Neo4j codebase since 2009 and have to tell you: 2009 Jim Webber couldn't imagine the way 2020 Neo4j would look. “2009 me” was building a REST API (if you've ever seen... read more


Check out this rapid retail example of Cypher query code for graph data recommendations.

Powering Recommendations with a Graph Database: A Rapid Retail Example

It’s one thing to say that Neo4j streamlines real-time recommendations; it’s another to show you the code so you can see for yourself. In this series, we discuss how real-time recommendations support a number of different use cases, from product recommendations to logistics. Last week,... read more


Discover how real-time recommendations support a number of different use cases that translate into business value.

Powering Recommendations with a Graph Database: Proven Business Benefits [+ Case Studies]

Relevant, real-time recommendations drive revenue, but they are challenging to deliver. That’s because good recommendations require bringing together so much data, surfacing the relationships between all that data and delivering just the right suggestion in context and in the moment. In... read more


Learn how graph database technology powers recommendation engines with connected data

Powering Recommendations with a Graph Database: Connect Buyer and Product Data

Effective recommendations increase revenue and drive up average order value. But delivering highly relevant, real-time recommendations requires as much context as possible. Connecting the user to the perfect recommendation is an art. In this three-part series, we explore using recommendations to... read more


Learn why the distinction of native graph databases matters when it comes to connect data

A Note on Native Graph Databases

It’s fun to watch the graph database category evolve. From being a seemingly niche category a decade ago (despite the valiant efforts of the Semantic Web community) to a modest – but important – pillar of the data world as it is today. But as the category has grown, we see some... read more


Learn how Neo4j's engineering evolved into the scalable native graph database that it is today

The Engineering Evolution of Neo4j into a Native Graph Database

Hi everyone. My name is Dr. Jim Webber. I'm Neo4j's chief scientist, and I'd like to take a few minutes to talk to you about Neo4j's evolution from an engineering point of view. Our Origin Story: Overcoming Complicated SQL Queries I don't know if many people know this, but Neo4j actually... read more


Learn why the native graph database distinction matters and how Neo4j grows with hardware capacity

The Co-Evolution of Computer Hardware & Graph Databases: Why Graph-Native Matters

Neo4j is a native graph database, which means all of the code – from the web browser to the drivers, Bolt protocol, page cache, cluster protocols, disk storage format — is optimized for graph workloads. As hardware advances come along, we’re uniquely positioned to adapt our software design to... read more


Watch Jim Webber’s Very Sciency Keynote Presentation on the Graph Database Landscape

Trekking Boldly into the Future: Going Who Knows Where in the Graph Space

Editor’s Note: Last October at GraphConnect San Francisco, Jim Webber – Chief Scientist at Neo Technology – delivered this very sciency closing keynote on the graph database landscape. For more videos from GraphConnect SF and to register for GraphConnect Europe, check out... read more


Learn More about the Competitive Advantage that Graph Databases Lend to Your Enterprise

The Competitive Advantage of Graph Databases in the Enterprise

“Big data” grows bigger every year, but today’s enterprise leaders don’t only need to manage larger volumes of data – they critically need to generate insight from their existing data. So how should CIOs and CTOs generate those insights? To paraphrase Seth Godin, businesses need to... read more


Learn More about the Graph-Based Search Use Case of Graph Databases in the Enterprise

Graph Databases in the Enterprise: Graph-Based Search

Graph-based search is a new approach to data and digital asset management originally pioneered by Facebook and Google. Search powered by a graph database delivers relevant information that you may not have specifically asked for – offering a more proactive and targeted search experience,... read more


Listen to Jim Webber’s Keynote Presentation on the History and Future of Graph Data Technologies

Impossible Is Nothing: The History (& Future) of Graph Data [GraphConnect Recap]

Editor’s Note: Last May at GraphConnect Europe, Jim Webber – Chief Scientist at Neo Technology – gave this inspiring (and nerdy) keynote talk on the history and future of graph data. Register for GraphConnect San Francisco to hear more speakers like Jim present on the emerging world of... read more