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Graph Algorithms: Examples in Spark and Neo4j
Sample code and tips for over 20 practical algorithms. Find vulnerabilities, detect communities, improve machine learning.Read Now
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What is Neo4j?
Neo4j is a native graph database, built from the ground up to leverage not only data but also data relationships. Neo4j connects data as it’s stored, enabling queries never before imagined, at speeds never thought possible.
The Native Graph Advantage
Unlike traditional databases, which arrange data in rows, columns and tables, Neo4j has a flexible structure defined by stored relationships between data records.
With Neo4j, each data record, or node, stores direct pointers to all the nodes it’s connected to. Because Neo4j is designed around this simple, yet powerful optimization, it performs queries with complex connections orders of magnitude faster, and with more depth, than other databases.Learn More
Cypher — The Graph Query Language
With Neo4j, connections between data are stored – not computed at query time. Cypher is a powerful, graph-optimized query language that understands, and takes advantage of, these stored connections.
When trying to find patterns or insights within data, Cypher queries are often much simpler and easier to write than massive SQL JOINs. Since Neo4j doesn’t have tables, there are no JOINs to worry about. For comparison with SQL, here's a simple Cypher query matching all products in a category hierarchy:
Here's a similar query in SQL, which is longer and more complex. Unlike Cypher, where depth is unlimited, this SQL query selects just three levels of depth.
Editor’s Note: This presentation was given by Corey Clawson at NODES 2019 in October 2019. Project Goals This project is an outgrowth of my graduate studies, which looked at archipelagic and archive studies, and analyzed what they have in common. Initial goals for this project included the ...Read More
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 problems? ...Read More
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, share my ...Read More