DBMS > Sadas Engine vs. SiteWhere vs. Transwarp ArgoDB

System Properties Comparison Sadas Engine vs. SiteWhere vs. Transwarp ArgoDB

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Editorial information provided by DB-Engines

Name

Description

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

M2M integration platform for persisting/querying time series data

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Search engine

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

Score	0.00
Rank	#381	Overall
	#156	Relational DBMS

Score	0.07
Rank	#346	Overall
	#31	Time Series DBMS

Score	0.01
Rank	#376	Overall
	#154	Relational DBMS

Website

www.sadasengine.com

github.com/sitewhere/sitewhere

www.transwarp.cn/en/product/argodb

Technical documentation

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

sitewhere1.sitewhere.io/index.html

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

SADAS s.r.l.

SiteWhere

Transwarp

Initial release

2006

2010

Current release

8.0

License

Commercial or Open Source

commercial

free trial version available

Open Source

Common Public Attribution License Version 1.0

commercial

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

AIX
Linux
Windows

Linux
OS X
Windows

Data scheme

yes

predefined 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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

HTTP REST

Supported programming languages

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

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

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

Transaction concepts

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

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

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

Users with fine-grained authorization concept

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