DBMS > IRONdb vs. OpenTSDB vs. OrigoDB vs. Sequoiadb

System Properties Comparison IRONdb vs. OpenTSDB vs. OrigoDB vs. Sequoiadb

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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

Scalable Time Series DBMS based on HBase

A fully ACID in-memory object graph database

NewSQL database with distributed OLTP and SQL

Primary database model

Time Series DBMS

Document store
Object oriented DBMS

Document store
Relational DBMS

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

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

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

opentsdb.net

origodb.com

www.sequoiadb.com

Technical documentation

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

opentsdb.net/docs/build/html/index.html

origodb.com/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Circonus LLC.

currently maintained by Yahoo and other contributors

Robert Friberg et al

Sequoiadb Ltd.

Initial release

2017

2011

2009

under the name LiveDB

2013

Current release

V0.10.20, January 2018

License

Commercial or Open Source

commercial

Open Source

LGPL

Open Source

Server: AGPL; Client: Apache V2

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++

Server operating systems

Linux

Linux
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

numeric data for metrics, strings for tags

User defined using .NET types and collections

yes

oid, date, timestamp, binary, regex

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

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

SQL-like query language

APIs and other access methods

HTTP API

HTTP API
Telnet API

.NET Client API
HTTP API
LINQ

proprietary protocol using JSON

Supported programming languages

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

Erlang
Go
Java
Python
R
Ruby

.Net

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes, in Lua

yes

JavaScript

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding

based on HBase

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

selectable replication factor

based on HBase

Source-replica replication

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

Immediate Consistency

based on HBase

Eventual Consistency

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Role based authorization

simple password-based access control

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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