DBMS > Graphite vs. IRONdb vs. Riak KV

System Properties Comparison Graphite vs. IRONdb vs. Riak KV

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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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

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

Distributed, fault tolerant key-value store

Primary database model

Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

github.com/graphite-project/graphite-web

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

Technical documentation

graphite.readthedocs.io

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

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Chris Davis

Circonus LLC.

OpenSource, formerly Basho Technologies

Initial release

2006

2017

2009

Current release

V0.10.20, January 2018

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache version 2, commercial enterprise edition

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

Python

C and C++

Erlang

Server operating systems

Linux
Unix

Linux

Linux
OS X

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

Numeric data only

yes

text, numeric, histograms

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

restricted

SQL

Support of SQL

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

APIs and other access methods

HTTP API
Sockets

HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

JavaScript (Node.js)
Python

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes, in Lua

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Automatic, metric affinity per node

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

none

configurable replication factor, datacenter aware

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

locking

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

yes, using Riak Security

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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

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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