DBMS > Amazon Redshift vs. Oracle Rdb vs. Sadas Engine vs. SiteWhere

System Properties Comparison Amazon Redshift vs. Oracle Rdb vs. Sadas Engine vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

aws.amazon.com/redshift

www.oracle.com/database/technologies/related/rdb.html

www.sadasengine.com

github.com/sitewhere/sitewhere

Technical documentation

docs.aws.amazon.com/redshift

www.oracle.com/database/technologies/related/rdb-doc.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

sitewhere1.sitewhere.io/index.html

Developer

Amazon (based on PostgreSQL)

Oracle, originally developed by Digital Equipment Corporation (DEC)

SADAS s.r.l.

SiteWhere

Initial release

2012

1984

2006

2010

Current release

7.4.1.1, 2021

8.0

License

Commercial or Open Source

commercial

free trial version available

Open Source

Common Public Attribution License Version 1.0

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

hosted

HP Open VMS

AIX
Linux
Windows

Linux
OS X
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Proprietary protocol

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

yes, on a single node

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

Users with fine-grained authorization concept

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