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GrapheneDB

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GrapheneDB vs Neo4j: What are the differences?

What is GrapheneDB? Cloud-hosted Neo4j Graph Databases as a Service. With automated backups, lightning-fast provisioning, 24x7 monitoring, and best-in-class support. Available on AWS, Azure and Heroku.

What is Neo4j? The world’s leading Graph Database. 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.

GrapheneDB belongs to "Graph Database as a Service" category of the tech stack, while Neo4j can be primarily classified under "Graph Databases".

Some of the features offered by GrapheneDB are:

  • Cloud scaling
  • Available in all major providers
  • 24x7 monitoring

On the other hand, Neo4j provides the following key features:

  • intuitive, using a graph model for data representation
  • reliable, with full ACID transactions
  • durable and fast, using a custom disk-based, native storage engine

Neo4j is an open source tool with 6.61K GitHub stars and 1.63K GitHub forks. Here's a link to Neo4j's open source repository on GitHub.

Advice on GrapheneDB and Neo4j
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 · 37.6K 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 GrapheneDB
Pros of Neo4j
    Be the first to leave a pro
    • 70
      Cypher – graph query language
    • 61
      Great graphdb
    • 33
      Open source
    • 31
      Rest api
    • 27
      High-Performance Native API
    • 24
      ACID
    • 21
      Easy setup
    • 17
      Great support
    • 11
      Clustering
    • 9
      Hot Backups
    • 8
      Great Web Admin UI
    • 7
      Mature
    • 7
      Powerful, flexible data model
    • 6
      Embeddable
    • 5
      Easy to Use and Model
    • 4
      Best Graphdb
    • 4
      Highly-available
    • 2
      Great onboarding process
    • 2
      It's awesome, I wanted to try it
    • 2
      Used by Crunchbase
    • 2
      Great query language and built in data browser

    Sign up to add or upvote prosMake informed product decisions

    Cons of GrapheneDB
    Cons of Neo4j
      Be the first to leave a con
      • 9
        Comparably slow
      • 4
        Can't store a vertex as JSON
      • 1
        Doesn't have a managed cloud service at low cost

      Sign up to add or upvote consMake informed product decisions

      - No public GitHub repository available -

      What is GrapheneDB?

      With automated backups, lightning-fast provisioning, 24x7 monitoring, and best-in-class support. Available on AWS, Azure and Heroku.

      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.

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

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

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      What are some alternatives to GrapheneDB and Neo4j?
      Amazon Neptune
      Amazon Neptune is a fast, reliable, fully-managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency.
      TigerGraph DB
      It is the only scalable graph database for the enterprise which is based on the industry’s first Native and Parallel Graph technology. It unleashes the power of interconnected data, offering organizations deeper insights and better outcomes. It’s proven technology supports applications such as IoT, AI and machine learning to make sense of ever-changing big data.
      Graph Story
      Graph Story offers fully-managed, fast, secure and affordable access to graph databases-as-a-service and makes them even easier to use through our customized API.
      See all alternatives