DBMS > OushuDB vs. searchxml vs. SiteWhere

System Properties Comparison OushuDB vs. searchxml vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

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

DBMS for structured and unstructured content wrapped with an application server

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Native XML DBMS
Search engine

Time Series DBMS

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

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

www.oushu.com/product/oushuDB

www.searchxml.net/category/products

github.com/sitewhere/sitewhere

Technical documentation

www.oushu.com/documentation

www.searchxml.net/support/handouts

sitewhere1.sitewhere.io/index.html

Developer

Oushu

informationpartners gmbh

SiteWhere

Initial release

2015

2010

Current release

4.0.1, August 2020

1.0

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

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++

Java

Server operating systems

Linux

Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

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

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC

RESTful HTTP API
WebDAV
XQuery
XSLT

HTTP REST

Supported programming languages

C
C++

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

sychronisation to multiple collections

selectable replication factor

based on HBase

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

Transaction concepts

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

ACID

multiple readers, single writer

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

Kerberos, SSL and role based access

Domain, group and role-based access control at the document level and for application services

Users with fine-grained authorization concept

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More resources

Recent citations in the news

China's answer to Snowflake is shaping as data demands upgrade
8 September 2021, PingWest

provided by Google News

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11 July 2017, Open Source For You

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9 March 2023, H2S Media

provided by Google News

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