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Amazon Neptune

52
132
+ 1
15
Neo4j

1K
1.2K
+ 1
352
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Amazon Neptune vs Neo4j: What are the differences?

Developers describe Amazon Neptune as "Fast, reliable graph database built for the cloud". 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. On the other hand, Neo4j is detailed as "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.

Amazon Neptune can be classified as a tool in the "Graph Database as a Service" category, while Neo4j is grouped under "Graph Databases".

Some of the features offered by Amazon Neptune are:

  • High performance and scalability
  • High availability and durability
  • Open Graph APIs

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.

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Pros of Amazon Neptune
Pros of Neo4j
  • 3
    Managed Service in AWS
  • 3
    High Performance
  • 2
    Support for RDF
  • 2
    Support for SPARQL
  • 2
    Easy to Use
  • 1
    ACID Compliant
  • 1
    Scalable
  • 1
    W3C Standards Compliantr
  • 70
    Cypher – graph query language
  • 61
    Great graphdb
  • 32
    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
    Powerful, flexible data model
  • 7
    Mature
  • 6
    Embeddable
  • 5
    Easy to Use and Model
  • 4
    Highly-available
  • 4
    Best Graphdb
  • 2
    Used by Crunchbase
  • 2
    Great onboarding process
  • 2
    It's awesome, I wanted to try it
  • 2
    Great query language and built in data browser

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Cons of Amazon Neptune
Cons of Neo4j
    Be the first to leave a con
    • 5
      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 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.

    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 Amazon Neptune?
    What companies use Neo4j?
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    What tools integrate with Amazon Neptune?
    What tools integrate with Neo4j?

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    What are some alternatives to Amazon Neptune and Neo4j?
    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.
    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.
    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.
    See all alternatives