DBMS > DataFS vs. Hawkular Metrics

System Properties Comparison DataFS vs. Hawkular Metrics

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Primary database model

Object oriented DBMS

Time Series DBMS

Secondary database models

Graph DBMS

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Score	0.00
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	#20	Object oriented DBMS

Score	0.01
Rank	#372	Overall
	#40	Time Series DBMS

Website

newdatabase.com

www.hawkular.org

Technical documentation

dev.mobiland.com/Overview.xsp

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

Developer

Mobiland AG

Community supported by Red Hat

Initial release

2018

2014

Current release

1.1.263, October 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

Java

Server operating systems

Windows

Linux
OS X
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

SQL

Support of SQL

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

HTTP REST

Supported programming languages

.Net
C
C#
C++
VB.Net

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

Triggers

no, except callback-events from server when changes happened

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Windows-Profile

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