DBMS > Cubrid vs. KairosDB vs. MonetDB vs. Trafodion

System Properties Comparison Cubrid vs. KairosDB vs. MonetDB vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. 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

Distributed Time Series DBMS based on Cassandra or H2

A relational database management system that stores data in columns

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	0.71
Rank	#230	Overall
	#20	Time Series DBMS

Score	1.72
Rank	#148	Overall
	#68	Relational DBMS

Website

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

github.com/kairosdb/kairosdb

www.monetdb.org

trafodion.apache.org

Technical documentation

cubrid.org/manuals

kairosdb.github.io

www.monetdb.org/Documentation

trafodion.apache.org/documentation.html

Developer

CUBRID Corporation, CUBRID Foundation

MonetDB BV

Apache Software Foundation, originally developed by HP

Initial release

2008

2013

2004

2014

Current release

11.0, January 2021

1.2.2, November 2018

Dec2023 (11.49), December 2023

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Mozilla Public License 2.0

Open Source

Apache 2.0

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++, Java

Server operating systems

Linux
Windows

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Graphite protocol
HTTP REST
Telnet API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

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

Java
JavaScript

Node.js
PHP
Python

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures

yes, in SQL, C, R

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

none

Source-replica replication available in experimental status

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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.

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

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