Neo4j with .NET

Document Databases, Map Reduce, Hadoop... NoSQL. Name a hype technology from the 2000s and chance is good I was a huge fanboy. Then I started working and realized: one of the few constants in our industry are Relational Database Management Systems. So by now I am a huge RDBMS fanboy (of course) and advertise to use SQL for everything.

My rule of thumb for every new project is:

When in doubt use PostgreSQL.

Wait... A Silver Bullet?

Well. Sometimes no matter how hard you try, no matter how often you iterate over your relational model, your queries are hell. A product of sweat, tears and 23 Joins stuck inside a chain of Common Table Expressions, that only a query planner could make sense of. It's hard to admit, but sometimes SQL doesn't fit.

That's the reason why I have taught myself how to work with Elasticsearch in .NET and Java, how to do Stream Data Processing with Apache Flink and Complex Event Processing for detecting complex patterns in temporal data.

I still advertise using a Relational Database as your Primary Datastore, but I also advertise to complement your relational data model with the best tools and data representations for the job at hand.

Enter Graph Databases

In real life you often have to deal complex many-to-many relationships in your data, think of big Social Networks. These networks have ever-evolving relationships in the data, that will be hard to add in a relational database. Also analyzing these relationships in a relational database and making sense of it becomes a very tedious job.

Microsoft has a perfect introduction to Graph Databases and their use cases :

What is a graph database

A graph database is a collection of nodes (or vertices) and edges (or relationships). A node represents an entity (for example, a person or an organization) and an edge represents a relationship between the two nodes that it connects (for example, likes or friends). Both nodes and edges may have properties associated with them. Here are some features that make a graph database unique:

  • Edges or relationships are first class entities in a Graph Database and can have attributes or properties associated with them.
  • A single edge can flexibly connect multiple nodes in a Graph Database.
  • You can express pattern matching and multi-hop navigation queries easily.
  • You can express transitive closure and polymorphic queries easily.

When to use a graph database

There is nothing a graph database can achieve, which cannot be achieved using a relational database. However, a graph database can make it easier to express certain kind of queries. Also, with specific optimizations, certain queries may perform better. Your decision to choose one over the other can be based on following factors:

  • Your application has hierarchical data. The HierarchyID datatype can be used to implement hierarchies, but it has some limitations. For example, it does not allow you to store multiple parents for a node.
  • Your application has complex many-to-many relationships; as application evolves, new relationships are added.
  • You need to analyze interconnected data and relationships.

Should I care? Do Graph Databases matter?

Graph database can be a very, very useful tool to simplify your life, when SQL queries become your painful enemy. But is it useful to learn about them? Do they matter? I think so, because parts of the industry are currently betting big on Graph data processing, like:

... Microsoft:

... or SAP:

... or Oracle:

So your database might already include Graph database capabilities!

On using Neo4j for the Article

So what Graph database should I use? The SQL Server 2017 Graph Database would be interesting, but it is at an early stage of development, and it comes with limited Cypher Query Language support. I don't have a SAP HANA License and no Oracle License at hand.

So I decided to base this Graph database example on Neo4j, which is the most popular Open Source Graph Database (according to the DB-Engines Ranking of Graph DBMS):

Neo4j is a graph database management system developed by Neo4j, Inc. Described by its developers as an ACID-compliant transactional database with native graph storage and processing, Neo4j is the most popular graph database according to DB-Engines ranking.

The Project: The Movie Database

The canonical Neo4j introduction is the Movie Database:

The movie database is a traditional dataset for graph databases, similiar to IMDB it contains movies and actors, directors, producers etc. It could be extended with Genres, Publishers, Ratings and more.

There are sample projects for Movie database applications in languages like Java, .NET, JavaScript, Python, Ruby, Elixir and even Haskell:

The Plan

All of the Movie Database sample projects deal with querying the dataset. As a developer I ask myself instantly: How is the data actually imported? How do you Bulk Insert data efficiently? It turns out, that the data import for the Movie database applications is done with CSV files and uses the Neo4j LOAD CSV statement:

In this article I will you show how to bulk insert data with the Neo4j .NET driver without using CSV files.

Source Code

The Source Code for this project can be found at:

Database Schema

The Graph data model is straightforward:

(:Movie {id, title})
(:Person {id, name​})
(:Genre {name})

(:Person)-[:ACTED_IN|:DIRECTED]→(:Movie)
(:Movie)-[:GENRE])→(:Genre)

Using the Neo4j Browser the Graph can be nicely visualized as a Graph and exported as SVG:

.NET Implementation

Installing the .NET Client

The Neo4jDotNetDriver is the officially supported .NET driver for Neo4j. It can be easily installed with NuGet:

PM> Install-Package Neo4j.Driver

Domain Model

Next we are translating the Graph Model into a Domain model. There is an additional entity MovieInformation, which is used to model the Relationships between Movies, Director, Genres and Cast.

// Copyright (c) Philipp Wagner. All rights reserved.
// Licensed under the MIT license. See LICENSE file in the project root for full license information.

using Newtonsoft.Json;

namespace Neo4JSample.Model
{
    public class Genre
    {
        [JsonProperty("name")]
        public string Name { get; set; }
    }

    public class Movie
    {
        [JsonProperty("id")]
        public string Id { get; set; }

        [JsonProperty("title")]
        public string Title { get; set; }
    }

    public class Person
    {
        [JsonProperty("id")]
        public string Id { get; set; }

        [JsonProperty("name")]
        public string Name { get; set; }
    }

    public class MovieInformation
    {
        [JsonProperty("movie")]
        public Movie Movie { get; set; }

        [JsonProperty("director")]
        public Person Director { get; set; }

        [JsonProperty("genres")]
        public IList<Genre> Genres { get; set; }

        [JsonProperty("cast")]
        public IList<Person> Cast { get; set; }
    }
}

Connection Settings

Next we are abstracting the Connection Settings away. You might feel like this is an unneccessary abstraction, but imagine you don't want to hardcode the Credentials anymore and want to load them with a Configuration file. If you inject the IConnectionSettings into a class, then all you have to do is implement the IConnectionSettings.

// Copyright (c) Philipp Wagner. All rights reserved.
// Licensed under the MIT license. See LICENSE file in the project root for full license information.

using Neo4j.Driver.V1;

namespace Neo4JSample.Settings
{
    public interface IConnectionSettings
    {
        string Uri { get; }

        IAuthToken AuthToken { get; }
    }

    public class ConnectionSettings : IConnectionSettings
    {
        public string Uri { get; private set; }

        public IAuthToken AuthToken { get; private set; }

        public ConnectionSettings(string uri, IAuthToken authToken)
        {
            Uri = uri;
            AuthToken = authToken;
        }

        public static ConnectionSettings CreateBasicAuth(string uri, string username, string password)
        {
            return new ConnectionSettings(uri, AuthTokens.Basic(username, password));
        }
    }
}

Parameter Serialization

There is a catch with the official Neo4j .NET Driver: It doesn't support user-defined types. In the Neo4j .NET driver source code this is explicitly mentioned (here):

/// <summary>
/// A helper method to explicitly cast the value streamed back via Bolt to a local type.
/// </summary>
/// <typeparam name="T">
/// Supports for the following types (or nullable version of the following types if applies):
/// ...
///
/// Undefined support for other types that are not listed above.
/// No support for user-defined types, e.g. Person, Movie.
/// </typeparam>

The Neo4j .NET driver expects you to pass your data as Dictionaries. So to overcome this issue I have used JSON.NET and serialize my domain model to JSON first and then deserialize it into a IDictionary<string, object> again. The nested user-defined objects also need to be deserialized as a IDictionary<string, object>.

To do this we need to define a Custom JSON Converter first:

// Copyright (c) Philipp Wagner. All rights reserved.
// Licensed under the MIT license. See LICENSE file in the project root for full license information.

using System;
using System.Collections.Generic;
using Newtonsoft.Json;

namespace Neo4JSample.Serializer.Converters
{
    /// <summary>
    /// This Converter is only a slightly modified converter from the JSON Extension library. 
    /// 
    /// All Credit goes to Oskar Gewalli (https://github.com/wallymathieu) and the Makrill Project (https://github.com/NewtonsoftJsonExt/makrill).
    /// </summary>
    public class CustomDictionaryConverter : JsonConverter
    {
        public override void WriteJson(JsonWriter writer, object value, JsonSerializer serializer)
        {
            serializer.Serialize(writer, value);
        }

        public override object ReadJson(JsonReader reader, Type objectType, object existingValue, JsonSerializer serializer)
        {
            return ExpectObject(reader);
        }

        private static object ExpectDictionaryOrArrayOrPrimitive(JsonReader reader)
        {
            reader.Read();
            var startToken = reader.TokenType;
            switch (startToken)
            {
                case JsonToken.String:
                case JsonToken.Integer:
                case JsonToken.Boolean:
                case JsonToken.Bytes:
                case JsonToken.Date:
                case JsonToken.Float:
                case JsonToken.Null:
                    return reader.Value;
                case JsonToken.StartObject:
                    return ExpectObject(reader);
                case JsonToken.StartArray:
                    return ExpectArray(reader);
            }
            throw new JsonSerializationException($"Unrecognized token: {reader.TokenType}");
        }

        private static object ExpectObject(JsonReader reader)
        {
            var dic = new Dictionary<string, object>();

            while (reader.Read())
            {
                switch (reader.TokenType)
                {
                    case JsonToken.Comment:
                        break;
                    case JsonToken.PropertyName:
                        dic.Add(reader.Value.ToString(), ExpectDictionaryOrArrayOrPrimitive(reader));
                        break;
                    case JsonToken.EndObject:
                        return dic;
                    default:
                        throw new JsonSerializationException($"Unrecognized token: {reader.TokenType}");
                }
            }
            throw new JsonSerializationException("Missing End Token");
        }

        private static object ExpectArray(JsonReader reader)
        {
            var array = new List<Object>();
            while (reader.Read())
            {
                switch (reader.TokenType)
                {
                    case JsonToken.String:
                    case JsonToken.Integer:
                    case JsonToken.Boolean:
                    case JsonToken.Bytes:
                    case JsonToken.Date:
                    case JsonToken.Float:
                    case JsonToken.Null:
                        array.Add(reader.Value);
                        break;
                    case JsonToken.Comment:
                        break;
                    case JsonToken.StartObject:
                        array.Add(ExpectObject(reader));
                        break;
                    case JsonToken.StartArray:
                        array.Add(ExpectArray(reader));
                        break;
                    case JsonToken.EndArray:
                        return array.ToArray();
                    default:
                        throw new JsonSerializationException($"Unrecognized token: {reader.TokenType}");
                }
            }
            throw new JsonSerializationException("Missing End Token");
        }

        public override bool CanConvert(Type objectType)
        {
            return objectType == typeof(Dictionary<string, object>);
        }
    }
}

And finally we can write a ParameterSerializer, which turns given list of user-defined types into a list of Dictionaries (with nested Dictionaries):

// Copyright (c) Philipp Wagner. All rights reserved.
// Licensed under the MIT license. See LICENSE file in the project root for full license information.

using System.Collections.Generic;
using Neo4JSample.Serializer.Converters;
using Newtonsoft.Json;

namespace Neo4JSample.Serializer
{
    public static class ParameterSerializer
    {
        public static IList<Dictionary<string, object>> ToDictionary<TSourceType>(IList<TSourceType> source)
        {
            var settings = new JsonSerializerSettings
            {
                NullValueHandling = NullValueHandling.Ignore
            };

            string json = JsonConvert.SerializeObject(source, settings);

            return JsonConvert.DeserializeObject<IList<Dictionary<string, object>>>(json, new CustomDictionaryConverter());
        }
    }
}

The Neo4j Client

Now we can implement the Neo4JClient to insert the Movie database. I am doing a lot of MERGE operations in the Cypher queries. So I am also adding indexes on the properties to provide faster lookups while inserting the data. I want the Client to be asynchronous, that's why I am exlusively using the Asynchronous API of the Neo4j .NET Driver.

You don't see any transaction handling in here, it's because the RunAsync automatically commits a transaction, if the Query was successful. For Bulk Inserts I have used the UNWIND operator for all the inserts, and the ParameterSerializer is used to prepare the user-defined types for the Neo4j .NET Driver.

// Copyright (c) Philipp Wagner. All rights reserved.
// Licensed under the MIT license. See LICENSE file in the project root for full license information.

using Neo4j.Driver.V1;
using Neo4JSample.Model;
using System;
using System.Collections.Generic;
using System.Text;
using System.Threading.Tasks;
using Neo4JSample.Serializer;
using Neo4JSample.Settings;

namespace Neo4JSample
{
    public class Neo4JClient : IDisposable
    {
        private readonly IDriver driver;

        public Neo4JClient(IConnectionSettings settings)
        {
            this.driver = GraphDatabase.Driver(settings.Uri, settings.AuthToken);
        }

        public async Task CreateIndices()
        {
            string[] queries = {
                "CREATE INDEX ON :Movie(title)",
                "CREATE INDEX ON :Movie(id)",
                "CREATE INDEX ON :Person(id)",
                "CREATE INDEX ON :Person(name)",
                "CREATE INDEX ON :Genre(name)"
            };

            using (var session = driver.Session())
            {
                foreach(var query in queries)
                {
                    await session.RunAsync(query);
                }
            }
        }

        public async Task CreatePersons(IList<Person> persons)
        {
            string cypher = new StringBuilder()
                .AppendLine("UNWIND {persons} AS person")
                .AppendLine("MERGE (p:Person {name: person.name})")
                .AppendLine("SET p = person")
                .ToString();

            using (var session = driver.Session())
            {
                await session.RunAsync(cypher, new Dictionary<string, object>() { { "persons", ParameterSerializer.ToDictionary(persons) } });
            }
        }

        public async Task CreateGenres(IList<Genre> genres)
        {
            string cypher = new StringBuilder()
                .AppendLine("UNWIND {genres} AS genre")
                .AppendLine("MERGE (g:Genre {name: genre.name})")
                .AppendLine("SET g = genre")
                .ToString();

            using (var session = driver.Session())
            {
                await session.RunAsync(cypher, new Dictionary<string, object>() { { "genres", ParameterSerializer.ToDictionary(genres) } });
            }
        }

        public async Task CreateMovies(IList<Movie> movies)
        {
            string cypher = new StringBuilder()
                .AppendLine("UNWIND {movies} AS movie")
                .AppendLine("MERGE (m:Movie {id: movie.id})")
                .AppendLine("SET m = movie")
                .ToString();

            using (var session = driver.Session())
            {
                await session.RunAsync(cypher, new Dictionary<string, object>() { { "movies", ParameterSerializer.ToDictionary(movies) } });
            }
        }

        public async Task CreateRelationships(IList<MovieInformation> metadatas)
        {
            string cypher = new StringBuilder()
                .AppendLine("UNWIND {metadatas} AS metadata")
                // Find the Movie:
                 .AppendLine("MATCH (m:Movie { title: metadata.movie.title })")
                 // Create Cast Relationships:
                 .AppendLine("UNWIND metadata.cast AS actor")   
                 .AppendLine("MATCH (a:Person { name: actor.name })")
                 .AppendLine("MERGE (a)-[r:ACTED_IN]->(m)")
                  // Create Director Relationship:
                 .AppendLine("WITH metadata, m")
                 .AppendLine("MATCH (d:Person { name: metadata.director.name })")
                 .AppendLine("MERGE (d)-[r:DIRECTED]->(m)")
                // Add Genres:
                .AppendLine("WITH metadata, m")
                .AppendLine("UNWIND metadata.genres AS genre")
                .AppendLine("MATCH (g:Genre { name: genre.name})")
                .AppendLine("MERGE (m)-[r:GENRE]->(g)")
                .ToString();


            using (var session = driver.Session())
            {
                await session.RunAsync(cypher, new Dictionary<string, object>() { { "metadatas", ParameterSerializer.ToDictionary(metadatas) } });
            }
        }

        public void Dispose()
        {
            driver?.Dispose();
        }
    }
}

Providing the Movie Database data

What's still left is the data. I decided to go with Mocked data first, but due to the IMovieDataService you can easily switch the implementation to a real datasource. Don't pin me on correctness of the movie information:

// Copyright (c) Philipp Wagner. All rights reserved.
// Licensed under the MIT license. See LICENSE file in the project root for full license information.

using Neo4JSample.Model;
using System.Collections.Generic;

namespace Neo4JSample.ConsoleApp.Services
{
    public interface IMovieDataService
    {
        IList<Genre> Genres { get; }

        IList<Person> Persons { get; }

        IList<Movie> Movies { get; }

        IList<MovieInformation> Metadatas { get; }
    }

    public class MovieDataService : IMovieDataService
    {
        private static Movie Movie0 = new Movie
        {
            Id = "1",
            Title = "Kill Bill"
        };

        private static Movie Movie1 = new Movie
        {
            Id = "2",
            Title = "Running Man"
        };

        private static Person Actor0 = new Person
        {
            Id = "1",
            Name = "Uma Thurman"
        };

        private static Person Actor1 = new Person
        {
            Id = "2",
            Name = "Arnold Schwarzenegger"
        };

        private static Person Director0 = new Person
        {
            Id = "3",
            Name = "Quentin Tarantino"
        };

        private static Person Director1 = new Person
        {
            Id = "3",
            Name = "Sergio Leone"
        };

        private static Genre Genre0 = new Genre
        {
            Name = "Romantic"
        };

        private static Genre Genre1 = new Genre
        {
            Name = "Action"
        };

        private static MovieInformation Metadata0 = new MovieInformation
        {
            Cast = new[] { Actor0 },
            Director = Director0,
            Genres = new[] { Genre0, Genre1 },
            Movie = Movie0
        };

        private static MovieInformation Metadata1 = new MovieInformation
        {
            Cast = new[] { Actor1 },
            Director = Director1,
            Genres = new[] { Genre1 },
            Movie = Movie1
        };

        public IList<Genre> Genres
        {
            get
            {
                return new[] { Genre0, Genre1 };
            }
        }

        public IList<Person> Persons
        {
            get
            {
                return new[] { Actor0, Actor1, Director0, Director1 };
            }
        }

        public IList<Movie> Movies
        {
            get
            {
                return new[] { Movie0, Movie1 };
            }
        }

        public IList<MovieInformation> Metadatas
        {
            get
            {
                return new[] { Metadata0, Metadata1 };
            }
        }
    }
}

Using the Movie Database Client

It looks like so much preliminary work just to insert some data. But with all the infrastructure code using our Neo4JClient and connecting the parts becomes really easy. You probably need to adjust the username and password to run the example against your Neo4j database:

// Copyright (c) Philipp Wagner. All rights reserved.
// Licensed under the MIT license. See LICENSE file in the project root for full license information.

using Neo4JSample.ConsoleApp.Services;
using System.Threading.Tasks;
using Neo4JSample.Settings;

namespace Neo4JSample.ConsoleApp
{
    internal class Program
    {
        public static void Main(string[] args)
        {
            var service = new MovieDataService();

            RunAsync(service).GetAwaiter().GetResult();
        }

        public static async Task RunAsync(IMovieDataService service)
        {
            var settings = ConnectionSettings.CreateBasicAuth("bolt://localhost:7687/db/actors", "neo4j", "test_pwd");

            using (var client = new Neo4JClient(settings))
            {

                // Create Indices for faster Lookups:
                await client.CreateIndices();

                // Create Base Data:
                await client.CreateMovies(service.Movies);
                await client.CreatePersons(service.Persons);
                await client.CreateGenres(service.Genres);

                // Create Relationships:
                await client.CreateRelationships(service.Metadatas);
            }
        }
    }
}

Querying the Data

Neo4j Browser

The Neo4j Browser is an excellent tool to query and visualize your data. To open the Neo4j Browser go to:

http://localhost:7474/browser/

It will show you the data we have just inserted:

So let's go ahead and query the graph!

Who acted in a Movie?

MATCH (m:Movie {title: 'Kill Bill'})<-[:ACTED_IN]-(a:Person)
RETURN a.name
╒═════════════╕
│"a.name"     │
╞═════════════╡
│"Uma Thurman"│
└─────────────┘

Which Action movies are available?

MATCH (g:Genre {name: 'Action'})<-[:GENRE]-(m:Movie)
RETURN m.title
╒═════════════╕
│"m.title"    │
╞═════════════╡
│"Running Man"│
├─────────────┤
│"Kill Bill"  │
└─────────────┘

Conclusion

Working with the official Neo4j .NET driver turned out to be more complicated, than I initially expected. But it was easy to overcome these issues with just a little infrastructure code, and it's now easier to use for upcoming projects. I think, that the Neo4j Browser is a great way to analyze and visualize your data and their relationships. I love the instant feedback!

The dataset in this article was admittedly tiny. In the next article I will investigate how Neo4j performs at scale.

How to contribute

One of the easiest ways to contribute is to participate in discussions. You can also contribute by submitting pull requests.

General feedback and discussions?

Do you have questions or feedback on this article? Please create an issue on the GitHub issue tracker.

Something is wrong or missing?

There may be something wrong or missing in this article. If you want to help fixing it, then please make a Pull Request to this file on GitHub.