DBMS > Hawkular Metrics vs. Kingbase vs. Quasardb vs. Splunk vs. TimesTen

System Properties Comparison Hawkular Metrics vs. Kingbase vs. Quasardb vs. Splunk 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.

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Distributed, high-performance timeseries database

Analytics Platform for Big Data

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

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	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

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

doc.quasar.ai/master

docs.splunk.com/Documentation/Splunk

docs.oracle.com/database/timesten-18.1

Developer

Community supported by Red Hat

BeiJing KINGBASE Information technologies inc.

quasardb

Splunk Inc.

Oracle, TimesTen Performance Software, HP

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

Initial release

2014

1999

2009

2003

1998

Current release

V8.0, August 2021

3.14.1, January 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

commercial

Limited free edition and free developer edition available

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.

Implementation language

Java

C and Java

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

BSD
Linux
OS X
Windows

Linux
OS X
Solaris
Windows

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

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

Splunk Search Processing Language for search commands

yes

APIs and other access methods

HTTP REST

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

HTTP API

HTTP REST

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
Python
Ruby

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C#
Java
JavaScript
PHP
Python
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

yes

PL/SQL

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

consistent hashing

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Source-replica replication with selectable replication factor

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

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

Transient mode

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

Access rights for users and roles

fine grained access rights according to SQL-standard

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