DBMS > OpenQM vs. OpenTSDB vs. RDF4J vs. RRDtool

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

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Editorial information provided by DB-Engines

Name

Description

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.

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

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

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

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

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

opentsdb.net

rdf4j.org

oss.oetiker.ch/rrdtool

Technical documentation

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

rdf4j.org/documentation

oss.oetiker.ch/rrdtool/doc

Developer

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.

Tobias Oetiker

Initial release

1993

2011

2004

1999

Current release

3.4-12

1.8.0, 2022

License

Commercial or Open Source

Open Source

GPLv2, extended commercial license available

Open Source

LGPL

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPL V2 and FLOSS

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

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
Windows

Linux
OS X
Unix
Windows

HP-UX
Linux

Data scheme

yes

with some exceptions

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

numeric data for metrics, strings for tags

yes

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

HTTP API
Telnet API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

in-process shared library
Pipes

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

Erlang
Go
Java
Python
R
Ruby

Java
PHP
Python

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

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

by using the rrdcached daemon

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

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

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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