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

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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 IN \$favorites
   RETURN rec.title as title, count(*) as freq 
   ORDER BY freq DESC LIMIT 5`;

var params = {"favorites": ["The Matrix"]};

var session = driver.session();

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);
  });

      

        # pip install neo4j-driver
# python example.py

from neo4j import GraphDatabase, basic_auth

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

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

results = session.run(cypher_query,
  parameters={"favorites":["The Matrix"]})

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

      

        //Install-Package Neo4j.Driver -Version 4.0.1
//Connecting to a 3.5.x Neo4j instance

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using Neo4j.Driver;

public class SimpleExample
{
	private readonly IDriver _driver;
	public SimpleExample(string uri, string user, string password)
	{
		_driver = GraphDatabase.Driver(uri, AuthTokens.Basic(user, password), builder => builder.WithEncryptionLevel(EncryptionLevel.None));
	}
	
	public async Task<IEnumerable<string>> GetMovieRecommendations(string favoriteMovieTitle)
	{
		var cypherQuery =
			  @$"MATCH (movie:Movie)<-[:ACTED_IN]-(actor)-[:ACTED_IN]->(rec:Movie) 
				WHERE movie.title IN ${nameof(favoriteMovieTitle)}
				RETURN rec.title AS title, count(*) AS freq
				ORDER BY freq DESC LIMIT 5";
		IAsyncSession session = _driver.AsyncSession();
		var runQuery = await session.ReadTransactionAsync(async tx =>
		{
			var result = await tx.RunAsync(cypherQuery, new { favoriteMovieTitle });
			return await result.ToListAsync();
		});
		await session?.CloseAsync();
		return runQuery.Select(q => q.Values["title"].As<string>());
	}
	
	public static void WriteToConsole(IEnumerable<string> titles)
	{
		foreach (var title in titles)
			Console.WriteLine(title);
	}
	
	public static async Task Main()
	{
		var example = new SimpleExample("bolt://<HOST>:<BOLTPORT>", "<USERNAME>", "<PASSWORD>");
		var movies = await example.GetMovieRecommendations("The Matrix");
		WriteToConsole(movies);
	}
}
      

        // 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
// javac -cp neo4j-java-driver-*.jar Example.java && java -cp neo4j-java-driver-*.jar:reactive-streams-*.jar:. Example

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

import java.util.List;
import static java.util.Arrays.asList;
import static java.util.Collections.singletonMap;

public class Example {

    public static void main(String...args) {
        Config noSSL = Config.builder().withoutEncryption().build();
        try (Driver driver = GraphDatabase.driver("bolt://<HOST>:<BOLTPORT>",AuthTokens.basic("<USERNAME>","<PASSWORD>"),noSSL);
		     Session session = driver.session()) {
            String cypherQuery =
                "MATCH (movie:Movie)<-[:ACTED_IN]-(actor)-[:ACTED_IN]->(rec:Movie) "+
                "WHERE movie.title IN $favorites "+
                "RETURN rec.title as title, count(*) as freq "+
                "ORDER BY freq DESC LIMIT 5";
            Result result = session.run(cypherQuery, parameters("favorites",asList("The Matrix")));
            while (result.hasNext()) {
                System.out.println(result.next().get("title").asString());
            }
	    }
    }
}



      

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Neo4j - The Fastest Path To Graph Success

Neo4j for RDBMS Developers

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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.

Professional Services

Neo4j Blog
5-Minute Interview: Graph-Powered Machine Learning with Dr. Alessandro Negro

We're very delighted to talk with Dr. Alessandro Negro, the Chief Scientist of GraphAware, who authored the recently published book, Graph-Powered Machine Learning. Dr. Negro has been a long-time member of the graph community, and was the main author of the very first recommendation engine based on ...

Neo4j Blog
Monitoring Neo4j Servers and Clusters

Editor’s Note: This presentation was given by David Allen at NODES 2019. Presentation Summary David Allen is a Partner Solution Architect at Neo4j. Today’s talk features monitoring clusters and single instances. Monitoring can be pretty dense and complicated. Neo4j exposes a couple of ...

Neo4j Blog
Combating Money Laundering: Graph Tech Fights Serious Crimes

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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August 6, 2020

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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 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
5-Minute Interview: Graph-Powered Machine Learning with Dr. Alessandro Negro

Neo4j Blog
Monitoring Neo4j Servers and Clusters

Neo4j Blog
Combating Money Laundering: Graph Tech Fights Serious Crimes

In the News

Best Graph Database: 2020 DBTA Readers’ Choice Award

Winners’ Circle: Neo4j

Content is king but context is queen

4 Ways to Excel as a Female Data Scientist

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 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 for RDBMS Developers

Bottom-line Impact

Graph Expertise

Neo4j Blog 5-Minute Interview: Graph-Powered Machine Learning with Dr. Alessandro Negro

Neo4j Blog Monitoring Neo4j Servers and Clusters

Neo4j Blog Combating Money Laundering: Graph Tech Fights Serious Crimes

In the News

Best Graph Database: 2020 DBTA Readers’ Choice Award

Winners’ Circle: Neo4j

Content is king but context is queen

4 Ways to Excel as a Female Data Scientist

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
5-Minute Interview: Graph-Powered Machine Learning with Dr. Alessandro Negro

Neo4j Blog
Monitoring Neo4j Servers and Clusters

Neo4j Blog
Combating Money Laundering: Graph Tech Fights Serious Crimes