DBMS > Cubrid vs. DataFS vs. Geode vs. IRONdb

System Properties Comparison Cubrid vs. DataFS vs. Geode vs. IRONdb

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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.

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Primary database model

Secondary database models

Graph DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Website

cubrid.com (korean)
cubrid.org (english)

newdatabase.com

geode.apache.org

www.circonus.com/solutions/time-series-database/

Technical documentation

cubrid.org/manuals

dev.mobiland.com/Overview.xsp

geode.apache.org/docs

docs.circonus.com/irondb/category/getting-started

Developer

CUBRID Corporation, CUBRID Foundation

Mobiland AG

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Circonus LLC.

Initial release

2008

2018

2002

2017

Current release

11.0, January 2021

1.1.263, October 2022

1.1, February 2017

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

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, C++, Java

Java

C and C++

Server operating systems

Linux
Windows

Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux

Data scheme

yes

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

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

yes

SQL-like query language (OQL)

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

.NET Client API
Proprietary client DLL
WinRT client

Java Client API
Memcached protocol
RESTful HTTP API

HTTP API

Supported programming languages

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

.Net
C
C#
C++
VB.Net

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

yes, in Lua

Triggers

yes

no, except callback-events from server when changes happened

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Proprietary Sharding system

Sharding

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

Windows-Profile

Access rights per client and object definable

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