Streaming Graphs: Combining Kafka and Neo4j

If you’re looking for the basics on how to turn streams into graphs with Neo4j and the Neo4j-Streams plugin, you’ve come to the right place.

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Turning Data Into Actionable Knowledge: 5-Minute Interview with David Meza

Check out this 5-minute interview with David Meza, Chief Knowledge Architect at Johnson Space Center, about how Neo4j has helped NASA.

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Bringing the Newly Approved GQL Project Into Focus

Learn more about the recently approved GQL project to to create a new declarative property graph query language and next steps.

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GQL Is Now a Global Standards Project alongside SQL

Learn how Graph Query Language (GQL) has just been approved to become an international standards project and what’s next for this graph database tech.

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Blazing Fast Recommendations: 5-Minute Interview with Tim Hanssen

Check out this 5-minute interview with Tim Hanssen, Founder and CTO of Mediaconnect, who uses Neo4j to build a real-time recommendation engine.

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Collaborative Technology Intelligence Platform

Discover how DuPont uses Neo4j to solve global challenges and share information with its diverse group of end users including scientists and engineers.

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Accelerating Digital Transformation at CA Technologies with Neo4j

Discover how CA Technologies used Neo4j to share enriched data between their sales, development and IT teams to create a company-wise database.

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Avoiding Database JOINs: 5-Minute Interview with Michael Wytock

In this 5-minute interview with Michael Wytock, CEO of Coshx, you’ll learn how a graph data model improves stackholder communications and more.

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Agile Open Source Intelligence: 5-Minute Interview with Frederick Kagan

“One thing that a relational database isn’t, is relational ,” said Frederick Kagan, Director of the Critical Threats Project at the American Enterprise Institute. All intelligence organizations are interested in seeing data connections and traversing networks. The Critical Threats Project… Read more →

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The Evolution and Future of Graph Technology: Intelligent Systems

The field of graph technology has developed rapidly in recent years. From the beginnings of the Neo4j graph database – released almost nine years ago in version 1.0 – up to the latest version (and also the developments of other… Read more →

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Graph Databases for Beginners: Why We Need NoSQL Databases

NoSQL databases are one of those things in life that are unhelpfully defined only by what they are not rather than by what they are, i.e., an anti-definition. NoSQL is a cheeky acronym for Not Only SQL – or more… Read more →

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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.… Read more →

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Imperative vs. Declarative Query Languages: What’s the Difference?

The evolution of programming languages has grown in parallel with the evolution of computing itself, with new languages being created with each new advance and paradigm shift. After all, if language shapes how we view reality, then changes in computing… Read more →

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Graph Databases for Beginners: Why a Database Query Language Matters (More Than You Think)

Languages (the natural, human kind) shape how you view the world. From color to time to gender relations, there’s no escaping how language limits (or expands) your worldview. Words are the categories and labels that we use to process and… Read more →

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Visualizing Healthy Lifestyles: 5-Minute Interview with Alicia Powers, SVP at NYCEDC

“The future of graph technology is already here. It’s everywhere, because we can model anything in a way that’s more close to how it is in real life,” said Alicia Powers, Senior Vice President at New York City Economic Development… Read more →

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It’s Time for a Single Property Graph Query Language [Vote Now]

The time has come to create a single, unified property graph query language. Different languages for different products help no one. We’ve heard from the graph community that a common query language would be powerful: more developers with transferable expertise;… Read more →

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Now You Can Express Cypher Queries in Pure Python using Pypher [Community Post]

Cypher is a pretty cool language. It allows you to easily manipulate and query your graph in a familiar – but at the same time – unique way. If you’re familiar with SQL, mixing in Cypher’s ASCII node and relationship… Read more →

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DevOps on Graphs:
The 5-Minute Interview with Ashley Sun, Software Engineer at LendingClub

“Basically, anything you can think of in your infrastructure, whether it’s GitHub, Jenkins, AWS, load balancers, Cisco UCS, vCenter – it’s all in our graph database,” said Ashley Sun, Software Engineer at LendingClub. DevOps at LendingClub is no easy feat:… Read more →

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Retail & Neo4j: Pricing & Revenue Management

It’s never been easier for customers to comparison shop. In a matter of minutes, customers can compare prices for a specific product across a dozen stores — and all from the comfort of home. They can even compare prices and… Read more →

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Retail & Neo4j: Supply Chain Visibility & Management

Now more than ever, supply chains are vast and complex. Products are often composed of different ingredients or parts that move through different vendors, and each of those parts may be composed of subparts, and the subparts may come from… Read more →

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How to Import the Bitcoin Blockchain into Neo4j [Community Post]

[As community content, this post reflects the views and opinions of the particular author and does not necessarily reflect the official stance of Neo4j.] This guide runs through the basic steps for importing the bitcoin blockchain into a Neo4j graph… Read more →

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Forrester Research: Graph Databases Vendor Landscape [Free Report]

In 2015, analyst firm Forrester Research published a vendor landscape report on the state of graph databases. It included a few graph technology vendors, several graph use cases and described Neo4j as the “most popular graph database.” Since then, graph… Read more →

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A Path to the Graph: Data Integration That Begins without Writing Any Code

Most people understand the problem in any large organization today is that the data is in silos. Data is disconnected, and as a result, a report from any one source is incomplete and not necessarily actionable to the extent it… Read more →

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Machine Learning, Graphs and the Fake News Epidemic (Part 2)

In last week’s post, we discussed why designing a fully automated fake news detector is currently infeasible and introduced a semi-automated, graph-based solution which would use machine learning to work alongside human fact checkers to scalably flag and quarantine fake… Read more →

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Financial Services & Neo4j: Anti-Money Laundering

Reducing the risk of money laundering presents a similar challenge to that of fraud detection when it comes to today’s financial services landscape. Firms need to know where funds come from and where they are headed, but criminals use indirection… Read more →

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