DBMS > Lovefield vs. openGauss vs. Tkrzw vs. Transwarp KunDB

System Properties Comparison Lovefield vs. openGauss vs. Tkrzw vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

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

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

google.github.io/lovefield

gitee.com/opengauss
opengauss.org

dbmx.net/tkrzw

www.transwarp.cn/en/product/kundb

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.opengauss.org/en
gitee.com/opengauss/docs

Developer

Google

Huawei and openGauss community

Mikio Hirabayashi

Transwarp

Initial release

2014

2019

2020

Current release

2.1.12, February 2017

3.0, March 2022

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

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

JavaScript

C, C++, Java

C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

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

SQL-like query language

via JavaScript builder pattern

ANSI SQL 2011

yes

APIs and other access methods

JDBC
ODBC

Supported programming languages

JavaScript

C
C++
Java

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash)

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

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, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

using specific database classes

User concepts

Access control

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

yes

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