DBMS > Cubrid vs. IBM Cloudant vs. JaguarDB vs. Sadas Engine

System Properties Comparison Cubrid vs. IBM Cloudant vs. JaguarDB vs. Sadas Engine

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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

Database as a Service offering based on Apache CouchDB

Performant, highly scalable DBMS for AI and IoT applications

SADAS Engine is a columnar DBMS specifically designed for high performance in Data warehouse environments

Primary database model

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

Score	1.20
Rank	#160	Overall
	#76	Relational DBMS

Score	3.47
Rank	#95	Overall
	#17	Document stores

Score	0.00
Rank	#354	Overall
	#54	Key-value stores

Score	0.00
Rank	#354	Overall
	#152	Relational DBMS

Website

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

www.ibm.com/cloud/cloudant

www.datajaguar.com

www.sadasengine.com

Technical documentation

cubrid.org/manuals

cloud.ibm.com/docs/Cloudant

www.datajaguar.com/support.php

www.sadasengine.com/index.php/downloads/documentation-columnar-db

Developer

CUBRID Corporation, CUBRID Foundation

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

DataJaguar, Inc.

SADAS s.r.l.

Initial release

2008

2010

2015

2006

Current release

11.0, January 2021

2.9.4 September 2018

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL V3.0

commercial

free trial version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Java

Erlang

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux
Windows

hosted

Linux

AIX
Linux
Windows

Data scheme

yes

schema-free

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP/JSON API

JDBC
ODBC

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

rights management via user accounts

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

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More resources

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26 September 2019, EnterpriseAI

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