DBMS > Amazon Redshift vs. InfinityDB vs. InfluxDB vs. IRONdb

System Properties Comparison Amazon Redshift vs. InfinityDB vs. InfluxDB vs. IRONdb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

A Java embedded Key-Value Store which extends the Java Map interface

DBMS for storing time series, events and metrics

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

Primary database model

Relational DBMS

Key-value store

Time Series DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.00
Rank	#383	Overall
	#59	Key-value stores

Score	22.12
Rank	#28	Overall
	#1	Time Series DBMS

Website

aws.amazon.com/redshift

boilerbay.com

www.influxdata.com/products/influxdb-overview

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

Technical documentation

docs.aws.amazon.com/redshift

boilerbay.com/infinitydb/manual

docs.influxdata.com/influxdb

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

Developer

Amazon (based on PostgreSQL)

Boiler Bay Inc.

Circonus LLC.

Initial release

2012

2002

2013

2017

Current release

4.0

2.7.6, April 2024

V0.10.20, January 2018

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Server operating systems

hosted

All OS with a Java VM

Linux
OS X

through Homebrew

Linux

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

Numeric data and Strings

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

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

APIs and other access methods

JDBC
ODBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

HTTP API
JSON over UDP

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Java

.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

Stored procedures

user defined functions

in Python

yes, in Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

in enterprise version only

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

in enterprise version only

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more

Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
» more

News

Real-Time Visualization for IIoT Data
24 September 2024

Deploying InfluxDB and Telegraf to Monitor Kubernetes
17 September 2024

Telegraf 1.32 Release Notes
13 September 2024

An Introductory Guide to Cloud Security for IIoT
12 September 2024

Building Real-Time Android Apps with InfluxDB Cloud: Data Logging, Querying, and Visualization
10 September 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.