Neo4j Graph Platform – The Leader in Graph Databases

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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.

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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

      MATCH (p:Product)-[:CATEGORY]->(l:ProductCategory)-[:PARENT*0..]->(:ProductCategory {name:"Dairy Products"})
RETURN p.name
    

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

      SELECT p.ProductName
FROM Product AS p
JOIN ProductCategory pc ON (p.CategoryID = pc.CategoryID AND pc.CategoryName = "Dairy Products")

JOIN ProductCategory pc1 ON (p.CategoryID = pc1.CategoryID)
JOIN ProductCategory pc2 ON (pc1.ParentID = pc2.CategoryID AND pc2.CategoryName = "Dairy Products")

JOIN ProductCategory pc3 ON (p.CategoryID = pc3.CategoryID)
JOIN ProductCategory pc4 ON (pc3.ParentID = pc4.CategoryID)
JOIN ProductCategory pc5 ON (pc4.ParentID = pc5.CategoryID AND pc5.CategoryName = "Dairy Products")
;
    

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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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        // npm install --save neo4j-driver
// node example.js
var neo4j = require('neo4j-driver');
var driver = neo4j.driver('bolt://<HOST>:<BOLTPORT>', 
                  neo4j.auth.basic('<USERNAME>', '<PASSWORD>'), 
                  {/* encrypted: 'ENCRYPTION_OFF' */});

var query = 
  `
  MATCH (movie:Movie)<-[:ACTED_IN]-(actor)-[:ACTED_IN]->(rec:Movie) 
  WHERE movie.title = $favorite 
  RETURN rec.title as title, count(*) as freq 
  ORDER BY freq DESC LIMIT 5 
  `;

var params = {"favorite": "The Matrix"};

var session = driver.session({database:"neo4j"});

session.run(query, params)
  .then(function(result) {
    result.records.forEach(function(record) {
        console.log(record.get('title'));
    })
	session.close();
    driver.close();
  })
  .catch(function(error) {
    console.log(error);
  });

      

        # pip3 install neo4j-driver
# python3 example.py

from neo4j import GraphDatabase, basic_auth

driver = GraphDatabase.driver(
  "bolt://<HOST>:<BOLTPORT>", 
  auth=basic_auth("<USERNAME>", "<PASSWORD>"))

cypher_query = '''
MATCH (movie:Movie)<-[:ACTED_IN]-(actor)-[:ACTED_IN]->(rec:Movie) 
WHERE movie.title = $favorite 
RETURN rec.title as title, count(*) as freq 
ORDER BY freq DESC LIMIT 5 
'''

with driver.session(database="neo4j") as session:
  results = session.read_transaction(
    lambda tx: tx.run(cypher_query,
      favorite="The Matrix").data())

  for record in results:
    print(record['title'])

driver.close()
      

        // install dotnet core on your system
// dotnet new console -o .
// dotnet add package Neo4j.Driver
// paste in this code into Program.cs
// dotnet run

using System;
using System.Collections.Generic;
using System.Text;
using System.Threading.Tasks;
using Neo4j.Driver;
  
namespace dotnet {
  class Example {
  static async Task Main() {
    var driver = GraphDatabase.Driver("bolt://<HOST>:<BOLTPORT>", 
                    AuthTokens.Basic("<USERNAME>", "<PASSWORD>"));

    var cypherQuery =
      @"
      MATCH (movie:Movie)<-[:ACTED_IN]-(actor)-[:ACTED_IN]->(rec:Movie) 
      WHERE movie.title = $favorite 
      RETURN rec.title as title, count(*) as freq 
      ORDER BY freq DESC LIMIT 5 
      ";

    var session = driver.AsyncSession(o => o.WithDatabase("neo4j"));
    var result = await session.ReadTransactionAsync(async tx => {
      var r = await tx.RunAsync(cypherQuery, 
              new { favorite="The Matrix"});
      return await r.ToListAsync();
    });

    await session?.CloseAsync();
    foreach (var row in result)
      Console.WriteLine(row["title"].As<string>());
	  
    }
  }
}
      

        // Add your the driver dependency to your pom.xml build.gradle etc.
// Java Driver Dependency: http://search.maven.org/#artifactdetails|org.neo4j.driver|neo4j-java-driver|4.0.1|jar
// Reactive Streams http://search.maven.org/#artifactdetails|org.reactivestreams|reactive-streams|1.0.3|jar
// download jars into current directory
// java -cp "*" Example.java

import org.neo4j.driver.*;
import static org.neo4j.driver.Values.parameters;

public class Example {

  public static void main(String...args) {

    Driver driver = GraphDatabase.driver("bolt://<HOST>:<BOLTPORT>",
              AuthTokens.basic("<USERNAME>","<PASSWORD>"));

    try (Session session = driver.session(SessionConfig.forDatabase("neo4j"))) {

      String cypherQuery =
        "MATCH (movie:Movie)<-[:ACTED_IN]-(actor)-[:ACTED_IN]->(rec:Movie) " +
        "WHERE movie.title = $favorite " +
        "RETURN rec.title as title, count(*) as freq " +
        "ORDER BY freq DESC LIMIT 5 " ;

      var result = session.readTransaction(
        tx -> tx.run(cypherQuery, 
                parameters("favorite","The Matrix"))
            .list());

      for (Record record : result) {
        System.out.println(record.get("title").asString());
      }
    }
    driver.close();
  }
}



      

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Neo4j Blog
Introducing Graph Databases For Dummies

Graph databases are the fastest growing database technology. Some people are drawn to graph databases for technical or performance reasons; others become interested because of the intuitive data model. One thing is clear: Graphs represent a departure from the relational and NoSQL models, but this ...

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Money laundering is among the hardest activities to detect in the world of financial crime. Funds move in plain sight through standard financial instruments, transactions, intermediaries, legal entities and institutions – avoiding detection by banks and law enforcement. The costs in regulatory fines and ...

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Fine-Grained Access Control for Better Security and Privacy

Fine-Grained Access Control for Security and Privacy

The world’s most flexible, reliable and developer–friendly graph database as a service.

Graph Databases For Dummies

Learn the basics of graph databases — from data modeling to deploying your first application

Graph Algorithms

New Data Science Code and Content

Why Neo4j?

Free O'Reilly Ebook
Graph Algorithms: Examples in Spark and Neo4j

No Download Required
Get Started Quickly with the Neo4j Sandbox

Free O'Reilly Ebook
Graph Databases
for Connected Data

What is Neo4j?

The Native Graph Advantage

Cypher — The Graph Query Language

Cypher

SQL

Use Your Favorite Programming Language

Neo4j - The Fastest Path To Graph Success

Neo4j for RDBMS Developers

Bottom-line Impact

Graph Expertise

Neo4j Blog
Introducing Graph Databases For Dummies

Neo4j Blog
Building Spatial Search Algorithms for Neo4j

Neo4j Blog
Combating Money Laundering: Graph Data Visualizations

In the News

So geht Datenanalytik für den Public Sector

On episode 50 of The Andy Show, Andy is joined by Dr Alexander Jarasche from DZD

Graph Tech Uncovers Coronavirus Aid Cybercrime

Cockroach Labs, Neo4j, Snowflake Talk Infrastructure Future

Neo4j Events

Case Study: Lockheed Martin

Fine-Grained Access Control for Better Security and Privacy

Fine-Grained Access Control for Security and Privacy

The world’s most flexible, reliable and developer–friendly graph database as a service.

Graph Databases For Dummies

Learn the basics of graph databases — from data modeling to deploying your first application

Graph Algorithms

New Data Science Code and Content

Why Neo4j?

Free O'Reilly Ebook Graph Algorithms: Examples in Spark and Neo4j

No Download Required Get Started Quickly with the Neo4j Sandbox

Free O'Reilly Ebook Graph Databasesfor Connected Data

What is Neo4j?

The Native Graph Advantage

Cypher — The Graph Query Language

Cypher

SQL

Use Your Favorite Programming Language

Neo4j for RDBMS Developers

Bottom-line Impact

Graph Expertise

Neo4j Blog Introducing Graph Databases For Dummies

Neo4j Blog Building Spatial Search Algorithms for Neo4j

Neo4j Blog Combating Money Laundering: Graph Data Visualizations

In the News

So geht Datenanalytik für den Public Sector

On episode 50 of The Andy Show, Andy is joined by Dr Alexander Jarasche from DZD

Graph Tech Uncovers Coronavirus Aid Cybercrime

Cockroach Labs, Neo4j, Snowflake Talk Infrastructure Future

Neo4j Events

Free O'Reilly Ebook
Graph Algorithms: Examples in Spark and Neo4j

No Download Required
Get Started Quickly with the Neo4j Sandbox

Free O'Reilly Ebook
Graph Databases
for Connected Data

Neo4j Blog
Introducing Graph Databases For Dummies

Neo4j Blog
Building Spatial Search Algorithms for Neo4j

Neo4j Blog
Combating Money Laundering: Graph Data Visualizations