DBMS > Amazon Redshift vs. CouchDB vs. IRONdb vs. Warp 10

System Properties Comparison Amazon Redshift vs. CouchDB vs. IRONdb vs. Warp 10

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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

Large scale data warehouse service for use with business intelligence tools

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Document store

Time Series DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/redshift

couchdb.apache.org

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

www.warp10.io

Technical documentation

docs.aws.amazon.com/redshift

docs.couchdb.org/en/stable

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

www.warp10.io/content/02_Getting_started

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Circonus LLC.

SenX

Initial release

2012

2005

2017

2015

Current release

3.3.3, December 2023

V0.10.20, January 2018

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

Apache License 2.0

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

Erlang

C and C++

Java

Server operating systems

hosted

Android
BSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

restricted

yes

via views

SQL

Support of SQL

yes

does not fully support an SQL-standard

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

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

.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

View functions in JavaScript

yes, in Lua

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Automatic, metric affinity per node

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

configurable replication factor, datacenter aware

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

atomic operations within a single document possible

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic 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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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