DBMS > Cubrid vs. Memcached vs. Postgres-XL vs. Tkrzw

System Properties Comparison Cubrid vs. Memcached vs. Postgres-XL vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

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

In-memory key-value store, originally intended for caching

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

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

www.memcached.org

www.postgres-xl.org

dbmx.net/tkrzw

Technical documentation

cubrid.org/manuals

github.com/memcached/memcached/wiki

www.postgres-xl.org/documentation

Developer

CUBRID Corporation, CUBRID Foundation

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Mikio Hirabayashi

Initial release

2008

2003

2014

since 2012, originally named StormDB

2020

Current release

11.0, January 2021

1.6.27, May 2024

10 R1, October 2018

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD license

Open Source

Mozilla public license

Open Source

Apache Version 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

C++

Server operating systems

Linux
Windows

FreeBSD
Linux
OS X
Unix
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

schema-free

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Proprietary protocol

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Redis extends the lead in the DB-Engines key-value store ranking
3 February 2014, Matthias Gelbmann

New DB-Engines Ranking shows the popularity of database management systems
3 October 2012, Matthias Gelbmann, Paul Andlinger

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