DBMS > Altibase vs. Amazon Neptune vs. Drizzle vs. Hawkular Metrics vs. RDF4J

System Properties Comparison Altibase vs. Amazon Neptune vs. Drizzle vs. Hawkular Metrics 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

An enterprise grade, high-performance RDBMS

Fast, reliable graph database built for the cloud

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

Primary database model

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

Score	0.87
Rank	#200	Overall
	#93	Relational DBMS

Score	2.20
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

altibase.com

aws.amazon.com/neptune

www.hawkular.org

rdf4j.org

Technical documentation

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

aws.amazon.com/neptune/developer-resources

www.hawkular.org/hawkular-metrics/docs/user-guide

rdf4j.org/documentation

Developer

Altibase

Amazon

Drizzle project, originally started by Brian Aker

Community supported by Red Hat

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

Initial release

1999

2017

2008

2014

2004

Current release

v7.3, 2023, August 2023

7.2.4, September 2012

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

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

AIX
HP-UX
Linux

hosted

FreeBSD
Linux
OS X

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL-92

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Proprietary protocol

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC

HTTP REST

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C++
Java

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C++
Java
PHP

Go
Java
Python
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

Triggers

yes

hooks for callbacks inside the server can be used.

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

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

with encyption-at-rest

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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