DBMS > AllegroGraph vs. Cloudflare Workers KV vs. H2GIS vs. Neo4j

System Properties Comparison AllegroGraph vs. Cloudflare Workers KV vs. H2GIS vs. Neo4j

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Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

Spatial extension of H2

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store

Key-value store

Spatial DBMS

Graph DBMS

Secondary database models

Spatial DBMS

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.15
Rank	#166	Overall
	#29	Document stores
	#14	Graph DBMS
	#7	RDF stores

Score	0.12
Rank	#305	Overall
	#45	Key-value stores

Score	0.03
Rank	#335	Overall
	#4	Spatial DBMS

Score	60.14
Rank	#19	Overall
	#1	Graph DBMS

Website

allegrograph.com

www.cloudflare.com/products/workers-kv

www.h2gis.org

neo4j.com

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

developers.cloudflare.com/workers/runtime-apis/kv

www.h2gis.org/docs/home

neo4j.com/docs

Developer

Franz Inc.

Cloudflare

CNRS

Neo4j, Inc.

Initial release

2004

2018

2013

2007

Current release

7.2.0, October 2021

4.4.7, May 2022

License

Commercial or Open Source

commercial

Limited community edition free

commercial

Open Source

LGPL 3.0

Open Source

GPL version3, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

Java

Java, Scala

Server operating systems

Linux
OS X
Windows

hosted

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

Data scheme

yes

RDF schemas

schema-free

yes

schema-free and schema-optional

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

bulk load of XML files possible

Secondary indexes

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

SPARQL is used as query language

yes

APIs and other access methods

RESTful HTTP API
SPARQL

HTTP REST
Proprietary protocol

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

Java

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

based on H2

yes

User defined Procedures and Functions

Triggers

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

yes using Neo4j Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

based on H2

Causal Clustering using Raft protocol

available in in Enterprise Version only

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

based on H2

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
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Neo4j delivers graph technology that has been battle tested for performance and scale...
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Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

Neo4j is the market leader, graph database category creator, and the most widely...
» more

Typical application scenarios

Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more

Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more

Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more

Licensing and pricing models

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more

News

The Knowledge Graph Conference 2022
4 May 2022

100 Companies That Matter – Franz Inc.
10 March 2022

Knowledge Graph Standards in Ambient Computing
15 February 2022

Linguistic Reduction and Knowledge Graphs for Next-Gen Chatbots
31 January 2022

Authentic Meets Artificial – The New Intelligence – DM Radio Broadcast
13 January 2022

This Week in Neo4j: Graph Composition, Cypher Tips, Dataset Analysis, Kafka Messages, Running Backups, Legal AI, and More
21 May 2022

How Knowledge Graphs Drive More Sales With Real-Time Recommendation Engines
20 May 2022

Our Journey to Self-Discovery: Synthesizing 30 Years of Data Pipelines With Knowledge Graphs
17 May 2022

How Knowledge Graphs Drive More Sales With Real-Time Recommendation Engines
16 May 2022

This Week in Neo4j: Graphs4Good, GraphQL, Game of Life, Information Extraction, Cypher Map Projection, and More
14 May 2022

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