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Graph Algorithms: Examples in Spark and Neo4j
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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.
Rik Van Bruggen invited special guest, Dr. Jim Webber, on a Graphistania podcast session to chat about Graph Databases For Dummies, a recently published book they co-authored. Graph Databases For Dummies, Neo4j Special Edition, is the first book Rik and Jim worked on together. Prior to this book, Rik ...Read More
A few weeks ago, we released Neo4j Bloom version 1.4 with new features to help you get started investigating graphs visually and providing new ways of viewing different types of graphs. We focused on these areas because, although people perform various types of activities in Bloom, it’s the ...Read More
We’re delighted to announce you can now take advantage of graph-native machine learning (ML) inside of Neo4j! We’ve just released a preview of Neo4j’s Graph Data Science™ Library version 1.4, which includes graph embeddings and an ML model catalog. Together, these enable you to create ...Read More