DBMS > DataFS vs. OpenQM vs. OpenTSDB vs. RDF4J

System Properties Comparison DataFS vs. OpenQM vs. OpenTSDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Scalable Time Series DBMS based on HBase

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

Primary database model

Secondary database models

Graph DBMS

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

newdatabase.com

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

opentsdb.net

rdf4j.org

Technical documentation

dev.mobiland.com/Overview.xsp

opentsdb.net/docs/build/html/index.html

rdf4j.org/documentation

Developer

Mobiland AG

Rocket Software, originally Martin Phillips

currently maintained by Yahoo and other contributors

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

Initial release

2018

1993

2011

2004

Current release

1.1.263, October 2022

3.4-12

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

LGPL

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

with some exceptions

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

HTTP API
Telnet API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C
C#
C++
VB.Net

.Net
Basic
C
Java
Objective C
PHP
Python

Erlang
Go
Java
Python
R
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

yes

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

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

In-memory capabilities

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

User concepts

Access control

Windows-Profile

Access rights can be defined down to the item level

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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