DBMS > Drizzle vs. Geode vs. Kinetica vs. MySQL vs. RDF4J

System Properties Comparison Drizzle vs. Geode vs. Kinetica vs. MySQL vs. RDF4J

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.

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Fully vectorized database across both GPUs and CPUs

Widely used open source RDBMS

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

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

RDF store

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

Technical documentation

geode.apache.org/docs

docs.kinetica.com

dev.mysql.com/doc

rdf4j.org/documentation

Developer

Drizzle project, originally started by Brian Aker

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Kinetica

Oracle

since 2010, originally MySQL AB, then Sun

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

Initial release

2008

2002

2012

1995

2004

Current release

7.2.4, September 2012

1.1, February 2017

7.1, August 2021

8.4.0, April 2024

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

C, C++

C and C++

Java

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

the JDK (8 or later) is also required

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (OQL)

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

JDBC

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

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

.Net
All JVM based languages
C++
Groovy
Java
Scala

C++
Java
JavaScript (Node.js)
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Cache Event Listeners

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

Source-replica replication

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

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

yes, on a single node

ACID

not for MyISAM storage engine

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights per client and object definable

Access rights for users and roles on table level

Users with fine-grained authorization concept

no user groups or roles

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