DBMS > JaguarDB vs. RDF4J vs. SWC-DB vs. Valentina Server

System Properties Comparison JaguarDB vs. RDF4J vs. SWC-DB vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

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

A high performance, scalable Wide Column DBMS

Object-relational database and reports server

Primary database model

Key-value store
Vector DBMS

RDF store

Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.09
Rank	#356	Overall
	#53	Key-value stores
	#13	Vector DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	0.01
Rank	#387	Overall
	#13	Wide column stores

Score	0.18
Rank	#329	Overall
	#144	Relational DBMS

Website

www.jaguardb.com

rdf4j.org

github.com/kashirin-alex/swc-db
www.swcdb.org

www.valentina-db.net

Technical documentation

www.jaguardb.com/support.html

rdf4j.org/documentation

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

DataJaguar, Inc.

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

Alex Kashirin

Paradigma Software

Initial release

2015

2004

2020

1999

Current release

3.3 July 2023

0.5, April 2021

5.7.5

License

Commercial or Open Source

Open Source

GPL V3.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPL V3

commercial

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

C++

the server part. Clients available in other languages

Java

C++

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

RDF Schemas

schema-free

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Proprietary protocol
Thrift

ODBC

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java
PHP
Python

C++

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

In-memory capabilities

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

yes

User concepts

Access control

rights management via user accounts

fine grained access rights according to SQL-standard

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