DBMS > gStore vs. Hawkular Metrics vs. Netezza vs. OrigoDB

System Properties Comparison gStore vs. Hawkular Metrics vs. Netezza vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Description

A native Graph DBMS to store and maintain very large RDF datasets.

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

Data warehouse and analytics appliance part of IBM PureSystems

A fully ACID in-memory object graph database

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Relational DBMS

Document store
Object oriented DBMS

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

Score	0.04
Rank	#359	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

en.gstore.cn

www.hawkular.org

www.ibm.com/products/netezza

origodb.com

Technical documentation

en.gstore.cn/#/enDocs

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

origodb.com/docs

Developer

Community supported by Red Hat

IBM

Robert Friberg et al

Initial release

2016

2014

2000

2009

under the name LiveDB

Current release

1.2, November 2023

License

Commercial or Open Source

Open Source

BSD

Open Source

Apache 2.0

commercial

Open Source

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++

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux

included in appliance

Linux
Windows

Data scheme

schema-free and OWL/RDFS-schema support

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP API
SPARQL 1.1

HTTP REST

JDBC
ODBC
OLE DB

.NET Client API
HTTP API
LINQ

Supported programming languages

C++
Java
JavaScript (Node.js)
PHP
Python

Go
Java
Python
Ruby

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

In-memory capabilities

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

yes

User concepts

Access control

Users, roles and permissions, Role-Based Access Control (RBAC) supported

Users with fine-grained authorization concept

Role based authorization

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