What is Neo4j?
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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.
Native Graph Database
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Neo4j for RDBMS Developers
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NODES 2020 is a free, multi-track, one-day virtual conference loaded with highly technical presentations delivered by Neo4j experts on graph-related topics. October 20, 2020 8:00 - 17:00 EDT | 12:00-21:00 GMT Last year was a hit! With five tracks, over 60 speakers across 15 countries, and 4,600 ...Read More
Interactive notebooks are rising in popularity and replacing PowerPoint presentations in many organizations. In this post, Larus Data Engineer Andrea Santurbano discusses how he uses Zeppelin and Neo4j in different contexts. Andrea helped build a Zeppelin Interpreter that connects directly to Neo4j ...Read More
Recommendation engines have become a crucial component of modern sales, finance, logistics and human resources applications. This core need has triggered a shift from relational and big-data approaches to graph-based technologies that are purpose-built to handle the rigorous demands of real-time ...Read More