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Graph Algorithms: Examples in Spark and Neo4j

Sample code and tips for over 20 practical graph algorithms. Find vulnerabilities, detect communities and improve machine learning.

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Get started with O'Reilly's Graph Databases and discover how graph databases can help you manage and query highly connected data.

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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 ssr破解版免费 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.

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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:

Cypher

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.

SQL

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Use Your Favorite Programming Language

Neo4j officially supports drivers for .Net, Java, JavaScript, Go and Python. Our community contributors provide many more, including PHP, Ruby, R, Erlang, Clojure and C/C++.

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Neo4j for RDBMS Developers

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Bottom-line Impact

Learn how companies are using graph databases to gain sustainable competitive advantage.

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Tap into an ecosystem of solutions and graph-based services to shorten your learning curve.

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Lju Lazarevic Picture

Neo4j Blog
Neo4j Bloom Tips and Tricks for Domain Knowledge Experts

Editor’s Note: This presentation was given by Lju Lazarevic at GraphConnect New York City in September 2018. Presentation Summary In this talk, Dr. Lazarevic will share some Neo4j Bloom tips and tricks for domain knowledge experts who don’t necessarily have a background in SQL and/or Cypher-led ...

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"Graph visualization helps with communication as well as analysis," said Amin Jalali, a researcher at Stockholm University. Complex problems are perfectly suited to a native graph database like Neo4j, which fully reflects the reality of vast connected data. Interactions between all the compounds in ...

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Designing the Enterprise: HR Applications at Scale

Editor’s Note: This presentation was given by Michael Moore, Todd Middlemis and Sameep Mondhe at GraphConnect New York in September 2018. Presentation Summary Michael Moore, Todd Middlemis and Sameep Mondhe work at EY as an executive director, partner and analytics strategist. EY was experiencing ...

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