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

Neo4j

1.2K
1.4K
+ 1
352
Neptune

14
37
+ 1
2
Add tool

Neo4j vs Neptune: What are the differences?

Introduction

Neo4j and Neptune are both powerful graph databases used for storing and querying highly connected data. While they share some similarities, they also have several key differences that set them apart from each other.

  1. Query Language:

    • Neo4j uses a proprietary query language called Cypher, which is specifically designed for querying graph data. It provides a simple and expressive syntax for traversing and manipulating the graph.
    • Neptune, on the other hand, supports query languages like Gremlin and SPARQL. Gremlin is a flexible graph traversal language, while SPARQL is a standard query language for RDF data. This gives Neptune the ability to work with other RDF datasets.
  2. Architecture:

    • Neo4j is a native graph database, which means it is built from the ground up to efficiently store and process graph data. It uses a property graph model, where nodes represent entities and relationships represent connections between them.
    • Neptune, on the other hand, is based on a columnar storage engine that is optimized for handling large-scale graphs. It uses a property graph model as well, but stores data in a columnar format for better performance and efficient disk utilization.
  3. Scalability:

    • Neo4j is designed to be highly scalable and can handle large amounts of data and complex queries. It supports horizontal scaling by distributing the graph across multiple machines, allowing for high availability and fault tolerance.
    • Neptune is also designed for scalability and can handle massive datasets. It uses a storage and query architecture that allows it to scale horizontally and automatically replicate data across multiple availability zones.
  4. Deployment Options:

    • Neo4j offers both on-premises and cloud-based deployment options. It can be installed and run on a single machine or distributed across a cluster of machines.
    • Neptune is a fully managed service provided by Amazon Web Services (AWS). It is only available as a cloud-based solution and is not available for on-premises deployment.
  5. Data Model:

    • Neo4j supports a flexible property graph model, where nodes can have properties and relationships can have properties as well. This allows for rich and complex data modeling.
    • Neptune also supports a property graph model, but it also has built-in support for RDF data. RDF is a standard model for representing and querying linked data, making Neptune suitable for applications that work with RDF datasets.
  6. Ecosystem and Community:

    • Neo4j has a mature ecosystem and a large and active community. It has a wide range of tools, libraries, and integrations that make it easy to develop and deploy graph-based applications. It also provides commercial support and training services.
    • Neptune is relatively newer compared to Neo4j, but it leverages the existing AWS ecosystem and infrastructure. It benefits from the scalability, security, and reliability provided by AWS and integrates well with other AWS services.

In summary, Neo4j and Neptune are both powerful graph databases, but they differ in terms of query language, architecture, scalability, deployment options, data model, and ecosystem.

Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
Pros of Neo4j
Pros of Neptune
  • 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
  • 1
    Aws managed services
  • 1
    Supports both gremlin and openCypher query languages

Sign up to add or upvote prosMake informed product decisions

Cons of Neo4j
Cons of Neptune
  • 9
    Comparably slow
  • 4
    Can't store a vertex as JSON
  • 1
    Doesn't have a managed cloud service at low cost
  • 1
    Doesn't have much support for openCypher clients
  • 1
    Doesn't have proper clients for different lanuages
  • 1
    Doesn't have much community support

Sign up to add or upvote consMake informed product decisions

- 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 Neptune?

It brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed, reproduced and shared with others. Works with all common technologies and integrates with other tools.

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

What companies use Neo4j?
What companies use Neptune?
See which teams inside your own company are using Neo4j or Neptune.
Sign up for StackShare EnterpriseLearn More

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with Neo4j?
What tools integrate with Neptune?

Sign up to get full access to all the tool integrationsMake informed product decisions

Blog Posts

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