DBMS > CouchDB vs. Faircom DB vs. Faircom EDGE vs. Oracle Rdb

System Properties Comparison CouchDB vs. Faircom DB vs. Faircom EDGE vs. Oracle Rdb

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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.

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

Primary database model

Document store

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

couchdb.apache.org

www.faircom.com/products/faircom-db

www.faircom.com/products/faircom-edge

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

docs.couchdb.org/en/stable

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Apache Software Foundation

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

FairCom Corporation

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2005

1979

1984

Current release

3.3.3, December 2023

V12, November 2020

V3, October 2020

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Restricted, free version available

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++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Android
Linux

ARM, x86
Raspbian
Windows

HP Open VMS

Data scheme

schema-free

schema free, schema optional, schema required, partial schema,

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

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes, ANSI Standard SQL Types

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.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

ANSI SQL queries

yes

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

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

Supported programming languages

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

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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

Server-side scripts

Stored procedures

View functions in JavaScript

yes

.Net, JavaScript, C/C++

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

File partitioning

Customizable business rules for partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes

Synchronous and asynchronous realtime replication based on transaction logs

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

atomic operations within a single document possible

tunable from ACID to Eventually Consistent

ACID

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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 access rights according to SQL-standard with additional protections for files

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

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