DBMS > gStore vs. Linter vs. OpenQM vs. RDF4J

System Properties Comparison gStore vs. Linter vs. OpenQM vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

A native Graph DBMS to store and maintain very large RDF datasets.

RDBMS for high security requirements

QpenQM is a high-performance, self-tuning, multi-value DBMS

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.03
Rank	#367	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	0.03
Rank	#368	Overall
	#156	Relational DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

en.gstore.cn

linter.ru

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

rdf4j.org

Technical documentation

en.gstore.cn/#/enDocs

rdf4j.org/documentation

Developer

relex.ru

Rocket Software, originally Martin Phillips

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

Initial release

2016

1990

1993

2004

Current release

1.2, November 2023

3.4-12

License

Commercial or Open Source

Open Source

BSD

commercial

Open Source

GPLv2, extended commercial license available

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

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Implementation language

C++

C and C++

Java

Server operating systems

Linux

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free and OWL/RDFS-schema support

yes

with some exceptions

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

APIs and other access methods

HTTP API
SPARQL 1.1

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C++
Java
JavaScript (Node.js)
PHP
Python

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

.Net
Basic
C
Java
Objective C
PHP
Python

Java
PHP
Python

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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.

User concepts

Access control

Users, roles and permissions, Role-Based Access Control (RBAC) supported

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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