DBMS > Oracle NoSQL vs. OushuDB vs. SiteWhere vs. Yanza

System Properties Comparison Oracle NoSQL vs. OushuDB vs. SiteWhere vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

M2M integration platform for persisting/querying time series data

Time Series DBMS for IoT Applications

Primary database model

Document store
Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

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

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

www.oracle.com/database/nosql/technologies/nosql

www.oushu.com/product/oushuDB

github.com/sitewhere/sitewhere

yanza.com

Technical documentation

docs.oracle.com/en/database/other-databases/nosql-database/index.html

www.oushu.com/documentation

sitewhere1.sitewhere.io/index.html

Developer

Oracle

Oushu

SiteWhere

Yanza

Initial release

2011

2010

2015

Current release

23.3, December 2023

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

Open Source

Common Public Attribution License Version 1.0

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

Linux
Solaris SPARC/x86

Linux

Linux
OS X
Windows

Windows

Data scheme

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

predefined scheme

schema-free

Typing

predefined data types such as float or date

optional

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

SQL-like DML and DDL statements

Full-featured ANSI SQL support

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

HTTP REST

HTTP API

Supported programming languages

C
C#
Go
Java
JavaScript (Node.js)
Python

C
C++

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

Access rights for users and roles

Kerberos, SSL and role based access

Users with fine-grained authorization concept

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