DBMS > Apache Kylin vs. Hawkular Metrics vs. IRONdb vs. MaxDB

System Properties Comparison Apache Kylin vs. Hawkular Metrics vs. IRONdb vs. MaxDB

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A robust and reliable RDBMS optimized to run all major SAP solutions

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Website

kylin.apache.org

www.hawkular.org

www.circonus.com/solutions/time-series-database/

maxdb.sap.com

Technical documentation

kylin.apache.org/docs

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

docs.circonus.com/irondb/category/getting-started

maxdb.sap.com/documentation

Developer

Apache Software Foundation, originally contributed from eBay Inc

Community supported by Red Hat

Circonus LLC.

SAP, acquired from Software AG (Adabas-D) in 1997

Initial release

2015

2014

2017

1984

Current release

3.1.0, July 2020

V0.10.20, January 2018

7.9.10.12, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Limited community edition free

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 C++

C++

Server operating systems

Linux

Linux
OS X
Windows

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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 for queries (using Apache Calcite)

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP REST

HTTP API

ADO.NET
JDBC
ODBC
WebDAV

Supported programming languages

Go
Java
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C#
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

yes, in Lua

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

configurable replication factor, datacenter aware

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

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

fine grained access rights according to SQL-standard

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