DBMS > Cubrid vs. Datomic vs. Firebird vs. OushuDB

System Properties Comparison Cubrid vs. Datomic vs. Firebird vs. OushuDB

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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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Firebird is an open source RDBMS forked from Borland's InterBase

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Relational DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Website

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

www.datomic.com

www.firebirdsql.org

www.oushu.com/product/oushuDB

Technical documentation

cubrid.org/manuals

docs.datomic.com

www.firebirdsql.org/en/reference-manuals

www.oushu.com/documentation

Developer

CUBRID Corporation, CUBRID Foundation

Cognitect

Firebird Foundation

Oushu

Initial release

2008

2012

2000

As fork of Borland's InterBase

Current release

11.0, January 2021

1.0.7075, December 2023

5.0.0, January 2024

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

limited edition free

Open Source

Initial Developer's Public License

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

Java, Clojure

C and C++

Server operating systems

Linux
Windows

All OS with a Java VM

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Full-featured ANSI SQL support

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

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

Clojure
Java

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C
C++

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Transaction Functions

PSQL

yes

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

But extensive use of caching in the application peers

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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

Features a multi-generational MVCC architecture, readers do not block writers

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

Kerberos, SSL and role based access

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