DBMS > IRONdb vs. KairosDB vs. SiteWhere vs. Trafodion

System Properties Comparison IRONdb vs. KairosDB vs. SiteWhere vs. Trafodion

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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.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Distributed Time Series DBMS based on Cassandra or H2

M2M integration platform for persisting/querying time series data

Transactional SQL-on-Hadoop DBMS

Primary database model

Time Series DBMS

Relational DBMS

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

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

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

github.com/kairosdb/kairosdb

github.com/sitewhere/sitewhere

trafodion.apache.org

Technical documentation

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

kairosdb.github.io

sitewhere1.sitewhere.io/index.html

trafodion.apache.org/documentation.html

Developer

Circonus LLC.

SiteWhere

Apache Software Foundation, originally developed by HP

Initial release

2017

2013

2010

2014

Current release

V0.10.20, January 2018

1.2.2, November 2018

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Common Public Attribution License Version 1.0

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

C and C++

Java

C++, Java

Server operating systems

Linux

Linux
OS X
Windows

Linux

Data scheme

schema-free

predefined scheme

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

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

yes

APIs and other access methods

HTTP API

Graphite protocol
HTTP REST
Telnet API

HTTP REST

ADO.NET
JDBC
ODBC

Supported programming languages

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

Java
JavaScript

Node.js
PHP
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes, in Lua

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding

based on Cassandra

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

selectable replication factor

based on Cassandra

selectable replication factor

based on HBase

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

simple password-based access control

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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