DBMS > NSDb vs. Oracle Rdb vs. Transwarp ArgoDB

System Properties Comparison NSDb vs. Oracle Rdb 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

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	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Website

nsdb.io

www.oracle.com/database/technologies/related/rdb.html

www.transwarp.cn/en/product/argodb

Technical documentation

nsdb.io/Architecture

www.oracle.com/database/technologies/related/rdb-doc.html

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

Developer

Oracle, originally developed by Digital Equipment Corporation (DEC)

Transwarp

Initial release

2017

1984

Current release

7.4.1.1, 2021

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

HP Open VMS

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

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

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

Supported programming languages

Java
Scala

Server-side scripts

Stored procedures

Partitioning methods

Methods for storing different data on different nodes

Sharding

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Using Apache Lucene

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

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