DBMS > CouchDB vs. Faircom EDGE vs. IRONdb

System Properties Comparison CouchDB vs. Faircom EDGE vs. IRONdb

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Editorial information provided by DB-Engines

Name

Description

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

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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

Primary database model

Document store

Key-value store
Relational DBMS

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	14.88
Rank	#41	Overall
	#7	Document stores

Score	0.01
Rank	#380	Overall
	#61	Key-value stores
	#156	Relational DBMS

Score	0.20
Rank	#334	Overall
	#28	Time Series DBMS

Website

couchdb.apache.org

www.faircom.com/products/faircomedge-iot-database

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

Technical documentation

docs.couchdb.org/en/stable

learn.faircomcorp.com/developers/documentation_directory

docs.circonus.com/irondb

Developer

Apache Software Foundation

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

FairCom Corporation

Circonus LLC.

Initial release

2005

1979

2017

Current release

3.3.0, January 2023

V3, October 2020

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Restricted, free version available

commercial

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

Erlang

ANSI C, C++

C and C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Android
Linux

ARM, x86
Raspbian
Windows

Linux

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

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.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

ANSI SQL queries

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

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

HTTP API

Supported programming languages

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

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

.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

View functions in JavaScript

yes

.Net, JavaScript, C/C++

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

File partitioning

Customizable business rules for partitioning

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Synchronous and asynchronous realtime replication based on transaction logs

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency
Tunable Consistency

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

across SQL and NoSQL

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

Access rights for users can be defined per database

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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More resources

DB-Engines blog posts

Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month
2 June 2014, Matthias Gelbmann

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Recent citations in the news

How to install the CouchDB NoSQL database on Debian Server 11
16 June 2022, TechRepublic

IBM Cloudant pulls plan to fund new foundational layer for CouchDB
15 March 2022, The Register

How to deploy CouchDB as a cluster with Docker
30 June 2022, TechRepublic

NoSQL Databases Software Market Demonstrates A Spectacular Growth By 2029 | Amazon, MarkLogic, RethinkDB
27 January 2023, openPR

Apache CouchDB 3.0 NoSQL Database: A Major Milestone -- ADTmag
27 February 2020, ADT Magazine

provided by Google News

Trend-Setting Products in Data and Information Management for 2023
8 December 2022, Database Trends and Applications

World's First Converged IIoT Hub to be Showcased at IoT Tech Expo
3 September 2021, Automation.com

Trend-Setting Products in Data and Information Management for 2022
8 December 2021, Database Trends and Applications

provided by Google News

Circonus Simplifies Monitoring & Observability for Large Enterprises
11 May 2022, PR Newswire

On the Radar: COVID-19, Circonus, and Fake FB Accounts
4 March 2020, Datanami

provided by Google News

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