DBMS > EsgynDB vs. IBM Db2 warehouse vs. OushuDB

System Properties Comparison EsgynDB vs. IBM Db2 warehouse vs. OushuDB

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Cloud-based data warehousing service

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	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Website

www.esgyn.cn

www.ibm.com/products/db2/warehouse

www.oushu.com/product/oushuDB

Technical documentation

www.oushu.com/documentation

Developer

Esgyn

IBM

Oushu

Initial release

2015

2014

Current release

4.0.1, August 2020

License

Commercial or Open Source

commercial

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++, Java

Server operating systems

Linux

hosted

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

Full-featured ANSI SQL support

APIs and other access methods

ADO.NET
JDBC
ODBC

.NET Client API
JDBC
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C++

Server-side scripts

Stored procedures

Java Stored Procedures

PL/SQL, SQL PL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

fine grained access rights according to SQL-standard

Kerberos, SSL and role based access

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