DBMS > Drizzle vs. Kyligence Enterprise vs. OushuDB vs. Yaacomo

System Properties Comparison Drizzle vs. Kyligence Enterprise vs. OushuDB vs. Yaacomo

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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.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

A distributed analytics engine for big data, built on top of Apache Kylin

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

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

Score	0.44
Rank	#259	Overall
	#118	Relational DBMS

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Website

kyligence.io/kyligence-enterprise

www.oushu.com/product/oushuDB

yaacomo.com

Technical documentation

www.oushu.com/documentation

Developer

Drizzle project, originally started by Brian Aker

Kyligence, Inc.

Oushu

Q2WEB GmbH

Initial release

2008

2016

2009

Current release

7.2.4, September 2012

4.0.1, August 2020

License

Commercial or Open Source

Open Source

GNU GPL

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++

Java

Server operating systems

FreeBSD
Linux
OS X

Linux

Android
Linux
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

with proprietary extensions

ANSI SQL for queries (using Apache Calcite)

Full-featured ANSI SQL support

yes

APIs and other access methods

JDBC

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
C++
Java
PHP

C
C++

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

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

In-memory capabilities

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

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Kerberos, SSL and role based access

fine grained access rights according to SQL-standard

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More resources

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