DBMS > NSDb vs. OushuDB vs. Transwarp ArgoDB

System Properties Comparison NSDb vs. OushuDB vs. Transwarp ArgoDB

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Editorial information provided by DB-Engines

Name

Description

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Search engine

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Website

nsdb.io

www.oushu.com/product/oushuDB

www.transwarp.cn/en/product/argodb

Technical documentation

nsdb.io/Architecture

www.oushu.com/documentation

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

Developer

Oushu

Transwarp

Initial release

2017

Current release

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Scala

Server operating systems

Linux
macOS

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

Full-featured ANSI SQL support

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

JDBC
ODBC

Supported programming languages

Java
Scala

C
C++

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

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

Using Apache Lucene

yes

User concepts

Access control

Kerberos, SSL and role based access

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