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
const neo4j = require('neo4j-driver');
const driver = neo4j.driver('bolt://<HOST>:<BOLTPORT>',
                  neo4j.auth.basic('<USERNAME>', '<PASSWORD>'), 
                  {/* encrypted: 'ENCRYPTION_OFF' */});

const query =
  `
  MATCH (p:Product)-[:PART_OF]->(:Category)-[:PARENT*0..]->
  (:Category {categoryName:$category})
  RETURN p.productName as product
  `;

const params = {"category": "Dairy Products"};

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

session.run(query, params)
  .then((result) => {
    result.records.forEach((record) => {
        console.log(record.get('product'));
    });
    session.close();
    driver.close();
  })
  .catch((error) => {
    console.error(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 (p:Product)-[:PART_OF]->(:Category)-[:PARENT*0..]->
(:Category {categoryName:$category})
RETURN p.productName as product
'''

with driver.session(database="neo4j") as session:
  results = session.read_transaction(
    lambda tx: tx.run(cypher_query,
      category="Dairy Products").data())

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

driver.close()
      

        // go mod init main
// go run example.go
package main
import (
	"fmt"
	"github.com/neo4j/neo4j-go-driver/neo4j" //Go 1.8
)
func main() {
	s, err := runQuery("bolt://<HOST>:<BOLTPORT>", "<USERNAME>", "<PASSWORD>")
	if err != nil {
		panic(err)
	}
	fmt.Println(s)
}
func runQuery(uri, username, password string) ([]string, error) {
	configForNeo4j4 := func(conf *neo4j.Config) { conf.Encrypted = false }
	driver, err := neo4j.NewDriver(uri, neo4j.BasicAuth(username, password, ""), configForNeo4j4)
	if err != nil {
		return nil, err
	}
	defer driver.Close()
	sessionConfig := neo4j.SessionConfig{AccessMode: neo4j.AccessModeRead, DatabaseName: "neo4j"}
	session, err := driver.NewSession(sessionConfig)
	if err != nil {
		return nil, err
	}
	defer session.Close()
	results, err := session.ReadTransaction(func(transaction neo4j.Transaction) (interface{}, error) {
		result, err := transaction.Run(
			`
			MATCH (p:Product)-[:PART_OF]->(:Category)-[:PARENT*0..]->
			(:Category {categoryName:$category})
			RETURN p.productName as product
			`, map[string]interface{}{
				"category": "Dairy Products",
			})
		if err != nil {
			return nil, err
		}
		var arr []string
		for result.Next() {
			value, found := result.Record().Get("product")
			if found {
			  arr = append(arr, value.(string))
			}
		}
		if err = result.Err(); err != nil {
			return nil, err
		}
		return arr, nil
	})
	if err != nil {
		return nil, err
	}
	return results.([]string), err
}
      

        // 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 (p:Product)-[:PART_OF]->(:Category)-[:PARENT*0..]->
      (:Category {categoryName:$category})
      RETURN p.productName as product
      ";

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

    await session?.CloseAsync();
    foreach (var row in result)
      Console.WriteLine(row["product"].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 (p:Product)-[:PART_OF]->(:Category)-[:PARENT*0..]->" +
        "(:Category {categoryName:$category})" +
        "RETURN p.productName as product";

      var result = session.readTransaction(
        tx -> tx.run(cypherQuery, 
                parameters("category","Dairy Products"))
            .list());

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



      

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Get an introduction to Neo4j with The Definitive Guide to Graph Databases for the RDBMS Developer.

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

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Neo4j Blog
Unearthing Historical Networks Using Neo4j and Archival Documents

Editor’s Note: This presentation was given by Corey Clawson at NODES 2019 in October 2019. Project Goals This project is an outgrowth of my graduate studies, which looked at archipelagic and archive studies, and analyzed what they have in common. Initial goals for this project included the ...

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Top 10 Use Cases: Empowering Network and IT Operations Management

Graph technology is the future. Not only do graph databases effectively store relationships between data points, but they’re also flexible in adding new kinds of relationships or adapting a data model to new business requirements. But how do companies today use graph databases to solve tough problems? ...

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Graphs for Artificial Intelligence and Machine Learning

Editor’s Note: This presentation was given by Dr. Jim Webber at GraphTour Boston in 2019. Full Presentation If there’s any area of computer science that’s prone to nonsense today, it’s artificial intelligence. I'm going to walk you through some no-nonsense definitions of AI-cronyms, share my ...

Case Study: Lockheed Martin

Neo4j Aura Enterprise

Neo4j's fully managed cloud service – the zero-admin, always-on graph database – now for the global enterprise

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

Neo4j Special Edition Graph Data Sciencefor Dummies

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 Unearthing Historical Networks Using Neo4j and Archival Documents

Neo4j Blog Top 10 Use Cases: Empowering Network and IT Operations Management

Neo4j Blog Graphs for Artificial Intelligence and Machine Learning

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

No Download Required
Get Started Quickly with the Neo4j Sandbox

Neo4j Special Edition
Graph Data Science
for Dummies

Neo4j Blog
Unearthing Historical Networks Using Neo4j and Archival Documents

Neo4j Blog
Top 10 Use Cases: Empowering Network and IT Operations Management

Neo4j Blog
Graphs for Artificial Intelligence and Machine Learning