DBMS > Newts vs. Sadas Engine vs. SiteWhere vs. Transbase

System Properties Comparison Newts vs. Sadas Engine vs. SiteWhere vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Time Series DBMS based on Cassandra

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

M2M integration platform for persisting/querying time series data

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

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

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

opennms.github.io/newts

www.sadasengine.com

github.com/sitewhere/sitewhere

www.transaction.de/en/products/transbase.html

Technical documentation

github.com/OpenNMS/newts/wiki

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

sitewhere1.sitewhere.io/index.html

www.transaction.de/en/products/transbase/features.html

Developer

OpenNMS Group

SADAS s.r.l.

SiteWhere

Transaction Software GmbH

Initial release

2014

2006

2010

1987

Current release

8.0

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free trial version available

Open Source

Common Public Attribution License Version 1.0

commercial

free development license

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

C and C++

Server operating systems

Linux
OS X
Windows

AIX
Linux
Windows

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

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

HTTP REST
Java API

JDBC
ODBC
Proprietary protocol

HTTP REST

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

selectable replication factor

based on HBase

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

fine grained access rights according to SQL-standard

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