DBMS > Hawkular Metrics vs. Kinetica vs. MySQL vs. OrigoDB vs. TimesTen

System Properties Comparison Hawkular Metrics vs. Kinetica vs. MySQL vs. OrigoDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

Fully vectorized database across both GPUs and CPUs

Widely used open source RDBMS

A fully ACID in-memory object graph database

In-Memory RDBMS compatible to Oracle

Primary database model

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Document store
Object oriented DBMS

Relational DBMS

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	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

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

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

docs.kinetica.com

dev.mysql.com/doc

origodb.com/docs

docs.oracle.com/database/timesten-18.1

Developer

Community supported by Red Hat

Kinetica

Oracle

since 2010, originally MySQL AB, then Sun

Robert Friberg et al

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2014

2012

1995

2009

under the name LiveDB

1998

Current release

7.1, August 2021

8.4.0, April 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

commercial

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.

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Implementation language

Java

C, C++

C and C++

Server operating systems

Linux
OS X
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

HTTP REST

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
HTTP API
LINQ

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
Python
Ruby

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

.Net

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

yes

PL/SQL

Triggers

yes

via Hawkular Alerting

yes

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

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

depending on model

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

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

Write ahead log

yes

by means of logfiles and checkpoints

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

Access rights for users and roles on table level

Users with fine-grained authorization concept

no user groups or roles

Role based authorization

fine grained access rights according to SQL-standard

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