DBMS > Drizzle vs. H2GIS vs. OushuDB

System Properties Comparison Drizzle vs. H2GIS vs. OushuDB

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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.

Spatial extension of H2

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

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Website

www.h2gis.org

www.oushu.com/product/oushuDB

Technical documentation

www.h2gis.org/docs/home

www.oushu.com/documentation

Developer

Drizzle project, originally started by Brian Aker

CNRS

Oushu

Initial release

2008

2013

Current release

7.2.4, September 2012

4.0.1, August 2020

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

LGPL 3.0

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++

Java

Server operating systems

FreeBSD
Linux
OS X

Linux

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

yes

Full-featured ANSI SQL support

APIs and other access methods

JDBC

JDBC
ODBC

Supported programming languages

C
C++
Java
PHP

Java

C
C++

Server-side scripts

Stored procedures

yes

based on H2

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

based on H2

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes, multi-version concurrency control (MVCC)

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

yes

based on H2

Kerberos, SSL and role based access

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