DBMS > RDF4J vs. STSdb vs. Transwarp StellarDB

System Properties Comparison RDF4J vs. STSdb vs. Transwarp StellarDB

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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.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

RDF store

Key-value store

Graph DBMS

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

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Website

rdf4j.org

github.com/STSSoft/STSdb4

www.transwarp.cn/en/product/stellardb

Technical documentation

rdf4j.org/documentation

Developer

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

STS Soft SC

Transwarp

Initial release

2004

2011

Current release

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPLv2, commercial license available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

Server operating systems

Linux
OS X
Unix
Windows

Windows

Data scheme

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

.NET Client API

OpenCypher

Supported programming languages

Java
PHP
Python

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Foreign keys

Referential integrity

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

in-memory storage is supported as well

yes

User concepts

Access control

yes

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