DBMS > Cubrid vs. Geode vs. Ingres vs. MySQL vs. RDFox

System Properties Comparison Cubrid vs. Geode vs. Ingres vs. MySQL vs. RDFox

Editorial information provided by DB-Engines

Name

Description

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

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

Well established RDBMS

Widely used open source RDBMS

High performance knowledge graph and semantic reasoning engine

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Graph DBMS
RDF store

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

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

Website

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

geode.apache.org

www.actian.com/databases/ingres

www.mysql.com

www.oxfordsemantic.tech

Technical documentation

cubrid.org/manuals

geode.apache.org/docs

docs.actian.com/ingres

dev.mysql.com/doc

docs.oxfordsemantic.tech

Developer

CUBRID Corporation, CUBRID Foundation

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

Actian Corporation

Oracle

since 2010, originally MySQL AB, then Sun

Oxford Semantic Technologies

Initial release

2008

2002

1974

originally developed at University Berkely in early 1970s

1995

2017

Current release

11.0, January 2021

1.1, February 2017

11.2, May 2022

8.4.0, April 2024

6.0, Septermber 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

Java

C and C++

C++

Server operating systems

Linux
Windows

All OS with a Java VM

the JDK (8 or later) is also required

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

RDF schemas

Typing

predefined data types such as float or date

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (OQL)

yes

with proprietary extensions

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Java Client API
Memcached protocol
RESTful HTTP API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API
SPARQL 1.1

Supported programming languages

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

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
Java

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

yes

proprietary syntax

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

Ingres Replicator

Multi-source replication
Source-replica replication

replication via a shared file system

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

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

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

yes, on a single node

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

table locks or row locks depending on storage engine

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

Access rights per client and object definable

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Roles, resources, and access types

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