DBMS > NSDb vs. Sadas Engine vs. Transwarp KunDB

System Properties Comparison NSDb vs. Sadas Engine vs. Transwarp KunDB

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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

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

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

Primary database model

Time Series DBMS

Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

nsdb.io

www.sadasengine.com

www.transwarp.cn/en/product/kundb

Technical documentation

nsdb.io/Architecture

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

Developer

SADAS s.r.l.

Transwarp

Initial release

2017

2006

Current release

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free trial version 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, Scala

C++

Server operating systems

Linux
macOS

AIX
Linux
Windows

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

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

JDBC
ODBC
Proprietary protocol

Supported programming languages

Java
Scala

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

ACID

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.

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

yes

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