GrapheneDB vs Neo4j

Overview

GrapheneDB

Stacks14

Followers27

Votes0

Neo4j

Stacks1.2K

Followers1.4K

Votes351

GitHub Stars15.3K

Forks2.5K

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.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Advice on GrapheneDB, Neo4j

Jaime

none at none

Aug 31, 2020

Needs advice

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.

56.4k views56.4k

Comments

Detailed Comparison

GrapheneDB	Neo4j
With automated backups, lightning-fast provisioning, 24x7 monitoring, and best-in-class support. Available on AWS, Azure and Heroku.	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.
Cloud scaling;Available in all major providers;24x7 monitoring;Expert support;Backups;Dashboard;Extensible;Pay as you go;Team collaboration	intuitive, using a graph model for data representation;reliable, with full ACID transactions;durable and fast, using a custom disk-based, native storage engine;massively scalable, up to several billion nodes/relationships/properties;highly-available, when distributed across multiple machines;expressive, with a powerful, human readable graph query language;fast, with a powerful traversal framework for high-speed graph queries;embeddable, with a few small jars;simple, accessible by a convenient REST interface or an object-oriented Java API
Statistics
GitHub Stars -	GitHub Stars 15.3K
GitHub Forks -	GitHub Forks 2.5K
Stacks 14	Stacks 1.2K
Followers 27	Followers 1.4K
Votes 0	Votes 351
Pros & Cons
No community feedback yet	Pros 69 Cypher – graph query language 61 Great graphdb 33 Open source 31 Rest api 27 High-Performance Native API Cons 9 Comparably slow 4 Can't store a vertex as JSON 1 Doesn't have a managed cloud service at low cost
Integrations
Microsoft Azure Heroku	No integrations available

What are some alternatives to GrapheneDB, Neo4j?

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.

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.

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.

RedisGraph

RedisGraph is a graph database developed from scratch on top of Redis, using the new Redis Modules API to extend Redis with new commands and capabilities. Its main features include: - Simple, fast indexing and querying - Data stored in RAM, using memory-efficient custom data structures - On disk persistence - Tabular result sets - Simple and popular graph query language (Cypher) - Data Filtering, Aggregation and ordering

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.

Blazegraph

It is a fully open-source high-performance graph database supporting the RDF data model and RDR. It operates as an embedded database or over a client/server REST API.

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 Engine

The distributed RAM store provides a globally addressable high-performance key-value store over a cluster of machines. Through the RAM store, GE enables the fast random data access power over a large distributed data set.

FalkorDB

FalkorDB is developing a novel graph database that revolutionizes the graph databases and AI industries. Our graph database is based on novel but proven linear algebra algorithms on sparse matrices that deliver unprecedented performance up to two orders of magnitude greater than the leading graph databases. Our goal is to provide the missing piece in AI in general and LLM in particular, reducing hallucinations and enhancing accuracy and reliability. We accomplish this by providing a fast and interactive knowledge graph, which provides a superior solution to the common solutions today.

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.

Related Comparisons

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.

GrapheneDB vs Neo4j