Neo4j Enables up to 100x Faster Analytics and Real-Time Decision-Making

Discover Neo4j’s new capabilities and features, including parallel runtime, native CDC, knowledge graph embeddings, and new algorithms.

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Native vs. Non-Native Graph Database

Discover the critical differences between native vs. non-native graph databases and why the distinctions matter for database performance.

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Announcing Neo4j Graph Data Science 2.3

We’re excited to announce Neo4j Graph Data Science 2.3, which includes new algorithms, new graph embedding, and performance improvements.

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Graph Databases for Beginners: Why Graph Technology Is the Future

The world of graph technology has changed (and is still changing), so we’re rebooting our “Graph Databases for Beginners” series to reflect what’s new in the world of graph tech – while also helping newcomers catch up to speed with… Read more →

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The Visual Simplicity of Graph: The 5-Minute Interview With Folks From Fractal 5

“Everything is a graph. So as far as Neo’s development and the advances it’s made in the speed and adoption of more data – and more mature data – everyone can leverage all the developments in regards to graph neural networks and such. And that lends itself to a better world altogether,” Bjartur Hjaltason, machine learning engineer at Fractal 5.

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How DBS Connect Knowledge with a Knowledge Quotient Framework

Discover how DBS brought their siloed customer data together using knowledge graphs to achieve customer 360.

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Better AI With Neo4j and Azure Machine Learning

Learn how to integrate Neo4j’s Graph Feature Engineering capabilities with Azure Machine Learning for better AI.

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A Machine Learning Innovation in Predictive Analytics

Discover how graph-based machine learning gives you more accurate predictions, using the CORA dataset as an example.

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Graphs for Cybersecurity: Knowledge Graph as Digital Twin

Learn how knowledge graphs help you defend against cyberattacks – from before it begins to until it ends as well as for subsequent analysis.

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Announcing NODES 2022!

Neo4j Online Developer Expo and Summit is back for 2022. The CFP is open. Submit your talks and share your stories with the graph community.

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Neo4j Integrates Into Your Data Ecosystem with Connectors

Developers and data scientists leverage many different technologies, each best suited for specific tasks: different types of databases, data warehouses, and data lakes, knit together with powerful ETL tools.

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Developers.Zed: The LinkedIn for Developers in Zambia

We had the pleasure of speaking with Kacha Mukabe, who is a grand winner of the 2021 Leonhard Euler Idea Contest for his innovative project using Neo4j graphs at Developers.Zed.

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Can’t Stop, Won’t Stop: Graph Data Science 2.1 Is Better Than Ever

With the latest release of our Graph Data Science library, not only do you get more algorithms than ever before, but you also get access to the easiest to use and most scalable framework available.

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Announcing Neo4j Bloom 2.3: Supercharged With Graph Data Science

With today’s latest release of Neo4j Bloom 2.3, we bring together the power of Graph Data Science and data visualization to AuraDS users and to anyone with Neo4j Graph Data Science Library setup on their databases.

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Graph Algorithms for Cybersecurity: A Picture Is Worth 1,000 Rows

Learn how cybersecurity firm Uplevel uses graph algorithms and analytics to detect malicious patterns and prevent cyberattacks.

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GraphConnect 2022: 10 Sessions You Don’t Want to Miss

Here are 10 highly-anticipated GraphConnect 2022 presentations (among 130+ sessions) that you don’t want to miss.

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New in 2022: Introducing Graph Data Science 2.0 and General Availability of AuraDS

Today, we’re celebrating the two-year anniversary Graph Data Science at Neo4j with some incredible advancements.

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Graph Embeddings: AI That Learns from Your Data to Solve Problems

Graph embeddings learn the structure of your connected data, revealing new ways to solve your pressing problems.

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Graph Data Science: The Secret to Accelerating Innovation with AI/ML

Learn how graph data science helps you accelerate innovation with AI, as well as supervised and unsupervised machine learning.

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Doctor.ai, a Voice Chatbot for Healthcare, Powered by Neo4j and AWS

A vast amount of relation-rich medical data is stored in graph databases on the cloud and processed by machine learning.

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Using a Hybrid Technique to Detect Illicit Activities in Shell Companies

See how Milind Tiwari detects fraudulent activities in shell companies using graph database and graph data science.

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Combining Knowledge Graph and Graph Algorithms to Find Hidden Skills at NASA

Check out how David Meza from NASA combined knowledge graph and graph algorithms to find hidden skills within the organization.

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The Bigger Picture: See IP Assets As an Interactive Dependencies Map

Learn how to visualize your intellectual property protection holistically to discover the gaps and evaluate their effects on dependent products and revenues.

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Gartner’s Getting Graphy at Highly Anticipated Data & Analytics Summit

Getting ready for the Gartner Data & Analytics Summit? Check out CMO of Neo4j Lance Walter’s anticipated list of sessions he’ll be attending.

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Happy One-Year Anniversary to Neo4j Graph Data Science!

We’re celebrating the one-year anniversary of Neo4j Graph Data Science and introducing new algorithms, ML capabilities, and more.

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