DBMS > 4D vs. Graph Engine vs. JanusGraph vs. RDF4J

System Properties Comparison 4D vs. Graph Engine vs. JanusGraph vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Graph DBMS

RDF store

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

Technical documentation

developer.4d.com

www.graphengine.io/docs/manual

docs.janusgraph.org

rdf4j.org/documentation

Developer

4D, Inc

Microsoft

Linux Foundation; originally developed as Titan by Aurelius

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

1984

2010

2017

2004

Current release

v20, April 2023

0.6.3, February 2023

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

.NET and C

Java

Server operating systems

OS X
Windows

.NET

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

4D proprietary IDE
PHP

C#
C++
F#
Visual Basic

Clojure
Java
Python

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

in-memory storage is supported as well

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 and groups

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

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Trinity
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