DBMS > Drizzle vs. RDF4J vs. SpatiaLite

System Properties Comparison Drizzle vs. RDF4J vs. SpatiaLite

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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.

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Spatial extension of SQLite

Primary database model

Relational DBMS

RDF store

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

rdf4j.org

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

rdf4j.org/documentation

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Drizzle project, originally started by Brian Aker

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Alessandro Furieri

Initial release

2008

2004

2008

Current release

7.2.4, September 2012

5.0.0, August 2020

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

C++

Server operating systems

FreeBSD
Linux
OS X

Linux
OS X
Unix
Windows

server-less

Data scheme

yes

RDF Schemas

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

APIs and other access methods

JDBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C++
Java
PHP

Java
PHP
Python

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

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

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More resources

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