DBMS > OushuDB vs. Valentina Server vs. Yaacomo

System Properties Comparison OushuDB vs. Valentina Server vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

Object-relational database and reports server

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

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

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

www.oushu.com/product/oushuDB

www.valentina-db.net

yaacomo.com

Technical documentation

www.oushu.com/documentation

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Oushu

Paradigma Software

Q2WEB GmbH

Initial release

1999

2009

Current release

4.0.1, August 2020

5.7.5

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Server operating systems

Linux

Linux
OS X
Windows

Android
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.

Secondary indexes

yes

SQL

Support of SQL

Full-featured ANSI SQL support

yes

APIs and other access methods

JDBC
ODBC

ODBC

JDBC
ODBC

Supported programming languages

C
C++

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

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

Kerberos, SSL and role based access

fine grained access rights according to SQL-standard

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More resources

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