DBMS > Atos Standard Common Repository vs. Cubrid vs. HyperSQL vs. Postgres-XL

System Properties Comparison Atos Standard Common Repository vs. Cubrid vs. HyperSQL vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Primary database model

Document store
Key-value store

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	3.90
Rank	#85	Overall
	#46	Relational DBMS

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

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

hsqldb.org

www.postgres-xl.org

Technical documentation

cubrid.org/manuals

hsqldb.org/web/hsqlDocsFrame.html

www.postgres-xl.org/documentation

Developer

Atos Convergence Creators

CUBRID Corporation, CUBRID Foundation

Initial release

2016

2008

2001

2014

since 2012, originally named StormDB

Current release

1703

11.0, January 2021

2.7.2, June 2023

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

based on BSD license

Open Source

Mozilla public license

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

Java

C, C++, Java

Java

Server operating systems

Linux

Linux
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
macOS

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

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

LDAP

ADO.NET
JDBC
ODBC
OLE DB

HTTP API

JDBC via HTTP
JDBC
ODBC

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

Supported programming languages

All languages with LDAP bindings

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

All languages supporting JDBC/ODBC
Java

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

Server-side scripts

Stored procedures

Java Stored Procedures

Java, SQL

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

horizontal partitioning

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 or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

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

User concepts

Access control

LDAP bind authentication

fine grained access rights according to SQL-standard

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