DBMS > Tigris vs. Transwarp KunDB vs. Valentina Server

System Properties Comparison Tigris vs. Transwarp KunDB vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

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

Object-relational database and reports server

Primary database model

Document store
Key-value store
Search engine
Time Series DBMS

Relational DBMS

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

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

www.tigrisdata.com

www.transwarp.cn/en/product/kundb

www.valentina-db.net

Technical documentation

www.tigrisdata.com/docs

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Tigris Data, Inc.

Transwarp

Paradigma Software

Initial release

2022

1999

Current release

5.7.5

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

Providers of DBaaS offerings, please contact us to be listed.

Server operating systems

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

yes

APIs and other access methods

CLI Client
gRPC
RESTful HTTP API

ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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, using FoundationDB

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

Access rights for users and roles

yes

fine grained access rights according to SQL-standard

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