DBMS > EJDB vs. LevelDB vs. Transwarp KunDB

System Properties Comparison EJDB vs. LevelDB vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

Primary database model

Document store

Key-value store

Relational DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

github.com/Softmotions/ejdb

github.com/google/leveldb

www.transwarp.cn/en/product/kundb

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

github.com/google/leveldb/blob/main/doc/index.md

Developer

Softmotions

Google

Transwarp

Initial release

2012

2011

Current release

1.23, February 2021

License

Commercial or Open Source

Open Source

GPLv2

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

server-less

Illumos
Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

in-process shared library

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

User concepts

Access control

yes

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