DBMS > GeoMesa vs. OpenQM vs. RDFox vs. RRDtool

System Properties Comparison GeoMesa vs. OpenQM vs. RDFox vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

High performance knowledge graph and semantic reasoning engine

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

Secondary database models

Relational DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Website

www.geomesa.org

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

www.oxfordsemantic.tech

oss.oetiker.ch/rrdtool

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

docs.oxfordsemantic.tech

oss.oetiker.ch/rrdtool/doc

Developer

CCRi and others

Rocket Software, originally Martin Phillips

Oxford Semantic Technologies

Tobias Oetiker

Initial release

2014

1993

2017

1999

Current release

5.0.0, May 2024

3.4-12

6.0, Septermber 2022

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GPLv2, extended commercial license available

commercial

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

Scala

C++

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

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
macOS
Windows

HP-UX
Linux

Data scheme

yes

with some exceptions

yes

RDF schemas

yes

Typing

predefined data types such as float or date

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

RESTful HTTP API
SPARQL 1.1

in-process shared library
Pipes

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

C
Java

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

depending on storage layer

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

replication via a shared file system

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

none

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

Durability

Support for making data persistent

yes

In-memory capabilities

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

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights can be defined down to the item level

Roles, resources, and access types

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, 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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