DBMS > JaguarDB vs. TerminusDB vs. Tkrzw vs. Transwarp KunDB

System Properties Comparison JaguarDB vs. TerminusDB vs. Tkrzw vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

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

Primary database model

Key-value store
Vector DBMS

Graph DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
RDF store

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

www.jaguardb.com

terminusdb.com

dbmx.net/tkrzw

www.transwarp.cn/en/product/kundb

Technical documentation

www.jaguardb.com/support.html

terminusdb.github.io/terminusdb/#

Developer

DataJaguar, Inc.

DataChemist Ltd.

Mikio Hirabayashi

Transwarp

Initial release

2015

2018

2020

Current release

3.3 July 2023

11.0.0, January 2023

0.9.3, August 2020

License

Commercial or Open Source

Open Source

GPL V3.0

Open Source

GPL V3

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.

Implementation language

C++

the server part. Clients available in other languages

Prolog, Rust

C++

Server operating systems

Linux

Linux
macOS

Data scheme

yes

schema-free

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language (WOQL)

yes

APIs and other access methods

JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript
Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Graph Partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Journaling Streams

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

yes

in-memory journaling

yes

In-memory capabilities

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

yes

using specific database classes

User concepts

Access control

rights management via user accounts

Role-based access control

yes

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More resources

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