DBMS > RDF4J vs. RDFox vs. VoltDB

System Properties Comparison RDF4J vs. RDFox vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

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

High performance knowledge graph and semantic reasoning engine

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

RDF store

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

rdf4j.org

www.oxfordsemantic.tech

www.voltdb.com

Technical documentation

rdf4j.org/documentation

docs.oxfordsemantic.tech

docs.voltdb.com

Developer

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

Oxford Semantic Technologies

VoltDB Inc.

Initial release

2004

2017

2010

Current release

6.0, Septermber 2022

11.3, April 2022

License

Commercial or Open Source

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

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

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Implementation language

Java

C++

Java, C++

Server operating systems

Linux
OS X
Unix
Windows

Linux
macOS
Windows

Linux
OS X

for development

Data scheme

yes

RDF Schemas

yes

RDF schemas

yes

Typing

predefined data types such as float or date

yes

Secondary indexes

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

RESTful HTTP API
SPARQL 1.1

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Java
PHP
Python

C
Java

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

replication via a shared file system

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

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

in-memory storage is supported as well

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

Roles, resources, and access types

Users and roles with access to stored procedures

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More resources

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