DBMS > Apache IoTDB vs. OushuDB vs. STSdb vs. Transwarp KunDB

System Properties Comparison Apache IoTDB vs. OushuDB vs. STSdb vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

iotdb.apache.org

www.oushu.com/product/oushuDB

github.com/STSSoft/STSdb4

www.transwarp.cn/en/product/kundb

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

www.oushu.com/documentation

Developer

Apache Software Foundation

Oushu

STS Soft SC

Transwarp

Initial release

2018

2011

Current release

1.1.0, April 2023

4.0.1, August 2020

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPLv2, commercial license available

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

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL-like query language

Full-featured ANSI SQL support

yes

APIs and other access methods

JDBC
Native API

JDBC
ODBC

.NET Client API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C++

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

yes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

yes

Kerberos, SSL and role based access

yes

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