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DBMS > InfluxDB vs. IRONdb

System Properties Comparison InfluxDB vs. IRONdb

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Editorial information provided by DB-Engines
NameInfluxDB  Xexclude from comparisonIRONdb  Xexclude from comparison
DescriptionDBMS for storing time series, events and metricsA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelTime Series DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.62
Rank#33  Overall
#1  Time Series DBMS
Score0.05
Rank#324  Overall
#28  Time Series DBMS
Websitewww.influxdata.com/­time-series-platform/­influxdbwww.irondb.io
Technical documentationdocs.influxdata.com/­influxdbwww.irondb.io/­docs
DeveloperCirconus LLC.
Initial release20132017
Current release1.7.8, August 2019V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoMIT-License; commercial enterprise version availablecommercial
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC and C++
Server operating systemsLinux
OS X infothrough Homebrew
Linux
Data schemeschema-freeschema-free
Typing infopredefined data types such as float or dateNumeric data and Stringsyes infotext, numeric, histograms
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesnono
SQL infoSupport of SQLSQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsHTTP API
JSON over UDP
HTTP API
Supported programming languages.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnoyes, in Lua
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoin enterprise version onlyAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoin enterprise version onlyconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoDepending on used storage engineno
User concepts infoAccess controlsimple rights management via user accountsno
More information provided by the system vendor
InfluxDBIRONdb
Specific characteristicsIRONdb is a highly available, distributed Time Series Database. It can support dozens...
» more
Competitive advantagesUnmatched Scalability IRONdb is unique among TSDBs in that it does not use a consensus...
» more
Typical application scenariosReal Systems Monitoring Monitor your systems infrastructure in real time across thousands...
» more
Key customersIRONdb serves the needs of the world's largest Time Series Database customers. One...
» more
Market metricsOnly TSDB capable of scaling to billions of metrics. Only TSDB to scale to dozens...
» more
Licensing and pricing modelsIRONdb is licensed under a subscription model based on the number of active metrics...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
InfluxDBIRONdb
DB-Engines blog posts

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

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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Recent citations in the news

InfluxDB Cloud 2.0 expands open source time series database
17 September 2019, TechTarget

InfluxData Releases Serverless Time Series Database for Cloud
23 September 2019, ADT Magazine

InfluxData launches InfluxDB Cloud 2.0 – the first serverless time series platform-as-a-service
10 September 2019, Business Wire

An Introduction to InfluxDB
5 August 2019, The Collegian

InfluxData unveils InfluxDB Cloud 2.0, a serverless time series platform
12 September 2019, Help Net Security

provided by Google News

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