DBMS > Drizzle vs. EJDB vs. Transwarp KunDB

System Properties Comparison Drizzle vs. EJDB vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

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

Primary database model

Relational DBMS

Document 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	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

github.com/Softmotions/ejdb

www.transwarp.cn/en/product/kundb

Technical documentation

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

Developer

Drizzle project, originally started by Brian Aker

Softmotions

Transwarp

Initial release

2008

2012

Current release

7.2.4, September 2012

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

GPLv2

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

FreeBSD
Linux
OS X

server-less

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

in-process shared library

Supported programming languages

C
C++
Java
PHP

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

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
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

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

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1 July 2013, Matthias Gelbmann

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