DBMS > Oracle NoSQL vs. Quasardb vs. SiteWhere

System Properties Comparison Oracle NoSQL vs. Quasardb vs. SiteWhere

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Editorial information provided by DB-Engines

Name

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

Distributed, high-performance timeseries database

M2M integration platform for persisting/querying time series data

Primary database model

Document store
Key-value store
Relational DBMS

Time Series DBMS

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

Score	2.96
Rank	#103	Overall
	#18	Document stores
	#17	Key-value stores
	#52	Relational DBMS

Score	0.19
Rank	#327	Overall
	#30	Time Series DBMS

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Website

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

quasar.ai

github.com/sitewhere/sitewhere

Technical documentation

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

doc.quasar.ai/master

sitewhere1.sitewhere.io/index.html

Developer

Oracle

quasardb

SiteWhere

Initial release

2011

2009

2010

Current release

23.3, December 2023

3.14.1, January 2024

License

Commercial or Open Source

Open Source

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

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

Java

C++

Java

Server operating systems

Linux
Solaris SPARC/x86

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

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

schema-free

predefined scheme

Typing

predefined data types such as float or date

optional

yes

integer and binary

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

with tags

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

RESTful HTTP API

HTTP API

HTTP REST

Supported programming languages

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

Sharding

based on HBase

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

Source-replica replication with selectable replication factor

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with 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

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

yes

Transient mode

User concepts

Access control

Access rights for users and roles

Cryptographically strong user authentication and audit trail

Users with fine-grained authorization concept

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