DBMS > mSQL vs. SiteWhere vs. Transwarp Hippo

System Properties Comparison mSQL vs. SiteWhere vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

mSQL (Mini SQL) is a simple and lightweight RDBMS

M2M integration platform for persisting/querying time series data

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Relational DBMS

Time Series DBMS

Vector DBMS

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

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

hughestech.com.au/products/msql

github.com/sitewhere/sitewhere

www.transwarp.cn/en/subproduct/hippo

Technical documentation

sitewhere1.sitewhere.io/index.html

Developer

Hughes Technologies

SiteWhere

Initial release

1994

2010

2023

Current release

4.4, October 2021

1.0, May 2023

License

Commercial or Open Source

commercial

free licenses can be provided

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

Java

C++

Server operating systems

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Windows

Linux
macOS

Data scheme

yes

predefined scheme

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

JDBC
ODBC

HTTP REST

RESTful HTTP API

Supported programming languages

C
C++
Delphi
Java
Perl
PHP
Tcl

C++
Java
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

Sharding

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

none

Immediate Consistency

Foreign keys

Referential integrity

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

User concepts

Access control

Users with fine-grained authorization concept

Role based access control and fine grained access rights

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