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Neo4j vs Titan: What are the differences?

Introduction

In this article, we will compare Neo4j and Titan, two popular graph databases, and highlight their key differences.

  1. Data Model: Neo4j follows a property graph model, where data is represented in the form of nodes, relationships, and properties. Titan, on the other hand, uses a distributed graph model, which enables scalability across multiple machines for handling large datasets efficiently.

  2. Scalability: While Neo4j can scale vertically by adding more resources to a single machine, it has limitations in terms of horizontal scalability. Titan, being a distributed graph database, can scale horizontally by adding more machines to the cluster, making it suitable for handling large-scale graph datasets.

  3. Storage Backend: Neo4j uses a native graph storage backend, where data is stored on disk in a proprietary format optimized for graph operations. Titan, on the other hand, supports multiple storage backends, including Apache Cassandra, Apache HBase, and others, making it more flexible in terms of storage options.

  4. Query Language: Neo4j uses the Cypher query language, which is a powerful and expressive language specially designed for querying and manipulating graph data. Titan, on the other hand, supports the Apache TinkerPop Gremlin query language, which is a general-purpose graph traversal language that works across different graph databases.

  5. Consistency vs Availability: Neo4j focuses on strong consistency, ensuring that all reads and writes to the database reflect the latest state of the data. Titan, on the other hand, emphasizes availability, trading off some degree of consistency for improved scalability and fault tolerance.

  6. Community and Ecosystem: Neo4j has a larger and more mature community, with a wide range of plugins, tools, and resources available for developers. Titan, although it has a smaller community, benefits from being part of the Apache Software Foundation, and therefore has the advantage of being associated with other popular and widely used projects.

In summary, Neo4j is a property graph database with a strong community and emphasis on consistency, while Titan is a distributed graph database with flexible storage options, horizontal scalability, and focus on availability.

Advice on Neo4j and Titan
Jaime Ramos
Needs advice
on
ArangoDBArangoDBDgraphDgraph
and
Neo4jNeo4j

Hi, I want to create a social network for students, and I was wondering which of these three Oriented Graph DB's would you recommend. I plan to implement machine learning algorithms such as k-means and others to give recommendations and some basic data analyses; also, everything is going to be hosted in the cloud, so I expect the DB to be hosted there. I want the queries to be as fast as possible, and I like good tools to monitor my data. I would appreciate any recommendations or thoughts.

Context:

I released the MVP 6 months ago and got almost 600 users just from my university in Colombia, But now I want to expand it all over my country. I am expecting more or less 20000 users.

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Replies (3)
Recommends
on
ArangoDBArangoDB

I have not used the others but I agree, ArangoDB should meet your needs. If you have worked with RDBMS and SQL before Arango will be a easy transition. AQL is simple yet powerful and deployment can be as small or large as you need. I love the fact that for my local development I can run it as docker container as part of my project and for production I can have multiple machines in a cluster. The project is also under active development and with the latest round of funding I feel comfortable that it will be around a while.

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David López Felguera
Full Stack Developer at NPAW · | 5 upvotes · 48.7K views
Recommends
on
ArangoDBArangoDB

Hi Jaime. I've worked with Neo4j and ArangoDB for a few years and for me, I prefer to use ArangoDB because its query sintax (AQL) is easier. I've built a network topology with both databases and now ArangoDB is the databases for that network topology. Also, ArangoDB has ArangoML that maybe can help you with your recommendation algorithims.

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Recommends
on
ArangoDBArangoDB

Hi Jaime, I work with Arango for about 3 years quite a lot. Before I do some investigation and choose ArangoDB against Neo4j due to multi-type DB, speed, and also clustering (but we do not use it now). Now we have RMDB and Graph working together. As others said, AQL is quite easy, but u can use some of the drivers like Java Spring, that get you to another level.. If you prefer more copy-paste with little rework, perhaps Neo4j can do the job for you, because there is a bigger community around it.. But I have to solve some issues with the ArangoDB community and its also fast. So I will preffere ArangoDB... Btw, there is a super easy Foxx Microservice tool on Arango that can help you solve basic things faster than write down robust BackEnd.

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Pros of Neo4j
Pros of Titan
  • 70
    Cypher – graph query language
  • 61
    Great graphdb
  • 33
    Open source
  • 31
    Rest api
  • 27
    High-Performance Native API
  • 23
    ACID
  • 21
    Easy setup
  • 17
    Great support
  • 11
    Clustering
  • 9
    Hot Backups
  • 8
    Great Web Admin UI
  • 7
    Powerful, flexible data model
  • 7
    Mature
  • 6
    Embeddable
  • 5
    Easy to Use and Model
  • 4
    Best Graphdb
  • 4
    Highly-available
  • 2
    It's awesome, I wanted to try it
  • 2
    Great onboarding process
  • 2
    Great query language and built in data browser
  • 2
    Used by Crunchbase
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    Cons of Neo4j
    Cons of Titan
    • 9
      Comparably slow
    • 4
      Can't store a vertex as JSON
    • 1
      Doesn't have a managed cloud service at low cost
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      - No public GitHub repository available -

      What is Neo4j?

      Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.

      What is Titan?

      Titan is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. Titan is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use Neo4j?
      What companies use Titan?
      See which teams inside your own company are using Neo4j or Titan.
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      What tools integrate with Neo4j?
      What tools integrate with Titan?

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      What are some alternatives to Neo4j and Titan?
      MongoDB
      MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
      Cassandra
      Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
      OrientDB
      It is an open source NoSQL database management system written in Java. It is a Multi-model database, supporting graph, document, key/value, and object models, but the relationships are managed as in graph databases with direct connections between records.
      JanusGraph
      It is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. It is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time.
      Dgraph
      Dgraph's goal is to provide Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. Dgraph supports GraphQL-like query syntax, and responds in JSON and Protocol Buffers over GRPC and HTTP.
      See all alternatives