DBMS > IRONdb vs. KairosDB vs. Oracle Berkeley DB vs. Sadas Engine

System Properties Comparison IRONdb vs. KairosDB vs. Oracle Berkeley DB vs. Sadas Engine

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

Distributed Time Series DBMS based on Cassandra or H2

Widely used in-process key-value store

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

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

Score	0.60
Rank	#238	Overall
	#20	Time Series DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

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

github.com/kairosdb/kairosdb

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

www.sadasengine.com

Technical documentation

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

kairosdb.github.io

docs.oracle.com/cd/E17076_05/html/index.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Circonus LLC.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

SADAS s.r.l.

Initial release

2017

2013

1994

2006

Current release

V0.10.20, January 2018

1.2.2, November 2018

18.1.40, May 2020

8.0

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

commercial license available

commercial

free trial version available

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, C++ (depending on the Berkeley DB edition)

C++

Server operating systems

Linux

Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

AIX
Linux
Windows

Data scheme

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

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

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

HTTP API

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC
Proprietary protocol

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes, in Lua

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding

based on Cassandra

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

selectable replication factor

based on Cassandra

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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.

yes

managed by 'Learn by Usage'

User concepts

Access control

simple password-based access control

Access rights for users, groups and roles according to SQL-standard

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