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Amazon Neptune

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15
Neo4j

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1.4K
+ 1
352
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Amazon Neptune vs Neo4j: What are the differences?

Amazon Neptune and Neo4j are two popular graph databases used for managing highly connected data. While both databases have similarities in terms of their graph-based nature, they have several key differences.

  1. Data Model: Amazon Neptune and Neo4j differ in their data modeling approaches. Neptune follows the property graph data model, where relationships between nodes and properties are explicitly defined. Neo4j, on the other hand, follows the labeled property graph model, allowing nodes and relationships to have labels which act as a way of grouping related entities. This distinction affects how data is structured and queried in each database.

  2. Scalability: Another distinguishing factor between Neptune and Neo4j is their scalability. Amazon Neptune is a fully managed graph database service that can easily scale horizontally by adding more Neptune instances. It leverages storage and compute resources in a highly scalable manner. Neo4j, on the other hand, is a distributed graph database that can be deployed across multiple instances, but requires more manual configuration and management to achieve scalability.

  3. Query Language: Neptune and Neo4j utilize different query languages. Neptune uses the Gremlin query language, a traversal-based language that enables users to interact with the graph database. Neo4j, on the other hand, uses Cypher as its query language, which provides a more declarative and intuitive way to express graph queries. The choice of query language can affect the ease of querying and expressing complex queries.

  4. Data Consistency: Amazon Neptune prioritizes high availability and durability over strict consistency. It follows an eventual consistency model, where updates to the database may take some time to propagate across all replicas. Neo4j, on the other hand, provides strong consistency guarantees, ensuring that data is immediately consistent across the distributed graph database. The choice between strong consistency and eventual consistency depends on the specific requirements of the application.

  5. Integration with Other Services: Neptune is tightly integrated with other AWS services, such as Amazon S3 for data backup, AWS Identity and Access Management (IAM) for access control, and AWS CloudTrail for auditing. This integration allows users to leverage the broader AWS ecosystem for various use cases. Neo4j, while not as tightly integrated with specific cloud services, can be easily integrated with different systems and frameworks through its extensive set of connectors and APIs.

In summary, Amazon Neptune and Neo4j differ in their data modeling approaches, scalability options, query languages, consistency models, and integration capabilities. The choice between the two depends on the specific requirements of the application and the level of control and flexibility needed in managing and querying graph data.

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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
    W3C Standards Compliantr
  • 1
    ACID Compliant
  • 1
    Scalable
  • 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 Amazon Neptune
Cons of Neo4j
  • 1
    No UI to see graph
  • 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 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 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.
JavaScript
JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles.
See all alternatives