DBMS > Altibase vs. Drizzle vs. EsgynDB vs. RDF4J vs. Riak KV

System Properties Comparison Altibase vs. Drizzle vs. EsgynDB vs. RDF4J vs. Riak KV

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

An enterprise grade, high-performance RDBMS

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

RDF store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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

Score	0.87
Rank	#200	Overall
	#93	Relational DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Website

altibase.com

www.esgyn.cn

rdf4j.org

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

rdf4j.org/documentation

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Altibase

Drizzle project, originally started by Brian Aker

Esgyn

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

OpenSource, formerly Basho Technologies

Initial release

1999

2008

2015

2004

2009

Current release

v7.3, 2023, August 2023

7.2.4, September 2012

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

GNU GPL

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache version 2, commercial enterprise edition

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++

C++, Java

Java

Erlang

Server operating systems

AIX
HP-UX
Linux

FreeBSD
Linux
OS X

Linux

Linux
OS X
Unix
Windows

Linux
OS X

Data scheme

yes

RDF Schemas

schema-free

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

restricted

SQL

Support of SQL

ANSI SQL-92

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API
Native Erlang Interface

Supported programming languages

C
C++
Java

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

Java
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

stored procedures and stored functions

Java Stored Procedures

yes

Erlang

Triggers

yes

hooks for callbacks inside the server can be used.

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

Isolation support depends on the API used

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

fine grained access rights according to SQL-standard

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

yes, using Riak Security

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