DBMS > Amazon Redshift vs. Cubrid vs. openGauss vs. Tkrzw

System Properties Comparison Amazon Redshift vs. Cubrid vs. openGauss vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

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

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.97
Rank	#189	Overall
	#86	Relational DBMS

Score	1.11
Rank	#175	Overall
	#79	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

aws.amazon.com/redshift

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

gitee.com/opengauss
opengauss.org

dbmx.net/tkrzw

Technical documentation

docs.aws.amazon.com/redshift

cubrid.org/manuals

docs.opengauss.org/en
gitee.com/opengauss/docs

Developer

Amazon (based on PostgreSQL)

CUBRID Corporation, CUBRID Foundation

Huawei and openGauss community

Mikio Hirabayashi

Initial release

2012

2008

2019

2020

Current release

11.0, January 2021

3.0, March 2022

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

C++

Server operating systems

hosted

Linux
Windows

Linux

Linux
macOS

Data scheme

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

ANSI SQL 2011

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

C
C++
Java

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning (by range, list and hash)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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

informational only, not enforced by the system

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.

yes

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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