DBMS > GeoSpock vs. Microsoft Azure Cosmos DB vs. OpenQM vs. RRDtool vs. SiteWhere

System Properties Comparison GeoSpock vs. Microsoft Azure Cosmos DB vs. OpenQM vs. RRDtool vs. SiteWhere

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

Globally distributed, horizontally scalable, multi-model database service

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

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.

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Multivalue DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

Spatial DBMS

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

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

geospock.com

azure.microsoft.com/services/cosmos-db

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

oss.oetiker.ch/rrdtool

github.com/sitewhere/sitewhere

Technical documentation

learn.microsoft.com/azure/cosmos-db

oss.oetiker.ch/rrdtool/doc

sitewhere1.sitewhere.io/index.html

Developer

GeoSpock

Microsoft

Rocket Software, originally Martin Phillips

Tobias Oetiker

SiteWhere

Initial release

2014

1993

1999

2010

Current release

2.0, September 2019

3.4-12

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

GPL V2 and FLOSS

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, Javascript

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

Java

Server operating systems

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

HP-UX
Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

with some exceptions

yes

predefined scheme

Typing

predefined data types such as float or date

yes

JSON types

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

temporal, categorical

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like query language

APIs and other access methods

JDBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

in-process shared library
Pipes

HTTP REST

Supported programming languages

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
Basic
C
Java
Objective C
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

JavaScript

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Implicit feature of the cloud service

yes

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes

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.

yes

User concepts

Access control

Access rights for users can be defined per table

Access rights can be defined down to the item level

Users with fine-grained authorization concept

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