DBMS > 4D vs. Cubrid vs. Transwarp StellarDB

System Properties Comparison 4D vs. Cubrid vs. Transwarp StellarDB

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Relational DBMS

Graph DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Website

www.4d.com

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

www.transwarp.cn/en/product/stellardb

Technical documentation

developer.4d.com

cubrid.org/manuals

Developer

4D, Inc

CUBRID Corporation, CUBRID Foundation

Transwarp

Initial release

1984

2008

Current release

v20, April 2023

11.0, January 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

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

Server operating systems

OS X
Windows

Linux
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

SQL-like query language

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

ADO.NET
JDBC
ODBC
OLE DB

OpenCypher

Supported programming languages

4D proprietary IDE
PHP

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

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

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

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

Users and groups

fine grained access rights according to SQL-standard

yes

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