DBMS > JanusGraph vs. RDF4J vs. VoltDB

System Properties Comparison JanusGraph vs. RDF4J vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

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.

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Graph DBMS

RDF store

Relational DBMS

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

Score	1.91
Rank	#135	Overall
	#12	Graph DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	1.46
Rank	#159	Overall
	#74	Relational DBMS

Website

janusgraph.org

rdf4j.org

www.voltdb.com

Technical documentation

docs.janusgraph.org

rdf4j.org/documentation

docs.voltdb.com

Developer

Linux Foundation; originally developed as Titan by Aurelius

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

VoltDB Inc.

Initial release

2017

2004

2010

Current release

0.6.3, February 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java

Java, C++

Server operating systems

Linux
OS X
Unix
Windows

Linux
OS X

for development

Data scheme

yes

RDF Schemas

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Clojure
Java
Python

Java
PHP
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

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

yes

in-memory storage is supported as well

yes

Snapshots and command logging

User concepts

Access control

User authentification and security via Rexster Graph Server

Users and roles with access to stored procedures

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More resources

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