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Dgraph vs Neo4j: What are the differences?

Key Differences between Dgraph and Neo4j

Dgraph and Neo4j are two popular graph databases with some key differences.

1. Data Sharding: Dgraph automatically shards data across multiple servers, allowing for efficient horizontal scaling. On the other hand, Neo4j does not have built-in support for data sharding, requiring manual distribution of data across different instances.

2. Query Language: Dgraph uses GraphQL+- as its query language, which enables developers to write expressive and efficient queries with complex filtering and aggregations. Neo4j, on the other hand, uses the Cypher query language, which is specifically designed for querying graph databases.

3. Architecture: Dgraph follows a distributed architecture, where data is distributed across multiple servers, providing high availability and fault tolerance. In contrast, Neo4j follows a single-server architecture, where all data is stored on a single instance.

4. ACID Compliance: Dgraph is designed to be eventually consistent, focusing more on horizontal scalability and performance, while sacrificing full ACID (Atomicity, Consistency, Isolation, Durability) compliance. Neo4j, on the other hand, offers strong consistency and full ACID compliance out of the box.

5. JSON-based Data Model: Dgraph natively supports a JSON-based data model, allowing for flexible and dynamic schema-less data storage. Neo4j uses a property graph model, where data is represented as nodes connected by relationships, providing more rigid schema enforcement.

6. Community and Ecosystem: While both Dgraph and Neo4j have active communities, Neo4j has a larger and more established ecosystem. Neo4j has been around for a longer time and has a wider range of community-contributed extensions and integrations.

In summary, Dgraph and Neo4j differ in terms of data sharding, query language, architecture, ACID compliance, data model, and ecosystem. Dgraph focuses on scalability and performance with automatic data sharding and a flexible JSON-based data model, while Neo4j offers strong consistency, ACID compliance, and a more established ecosystem.

Advice on Dgraph 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 · 47.8K 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 Dgraph
Pros of Neo4j
  • 3
    Graphql as a query language is nice if you like apollo
  • 2
    Easy set up
  • 2
    Low learning curve
  • 1
    Open Source
  • 1
    High Performance
  • 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 Dgraph
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

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    What is 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.

    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.

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    What companies use Dgraph?
    What companies use Neo4j?
    See which teams inside your own company are using Dgraph or Neo4j.
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    What tools integrate with Dgraph?
    What tools integrate with Neo4j?
      No integrations found

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      What are some alternatives to Dgraph and Neo4j?
      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.
      ArangoDB
      A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.
      Cayley
      Cayley is an open-source graph inspired by the graph database behind Freebase and Google's Knowledge Graph. Its goal is to be a part of the developer's toolbox where Linked Data and graph-shaped data (semantic webs, social networks, etc) in general are concerned.
      GraphQL
      GraphQL is a data query language and runtime designed and used at Facebook to request and deliver data to mobile and web apps since 2012.
      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.
      See all alternatives