DBMS > CouchDB vs. Faircom EDGE vs. Microsoft Azure SQL Database vs. PouchDB vs. RocksDB

System Properties Comparison CouchDB vs. Faircom EDGE vs. Microsoft Azure SQL Database vs. PouchDB vs. RocksDB

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

Database as a Service offering with high compatibility to Microsoft SQL Server

JavaScript DBMS with an API inspired by CouchDB

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store

Key-value store
Relational DBMS

Relational DBMS

Document store

Key-value store

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Graph DBMS
Spatial DBMS

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

couchdb.apache.org

www.faircom.com/products/faircom-edge

azure.microsoft.com/en-us/products/azure-sql/database

pouchdb.com

rocksdb.org

Technical documentation

docs.couchdb.org/en/stable

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

docs.microsoft.com/en-us/azure/azure-sql

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

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

FairCom Corporation

Microsoft

Apache Software Foundation

Facebook, Inc.

Initial release

2005

1979

2010

2012

2013

Current release

3.3.3, December 2023

V3, October 2020

V12

7.1.1, June 2019

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Restricted, free version available

commercial

Open Source

BSD

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

ANSI C, C++

C++

JavaScript

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Android
Linux

ARM, x86
Raspbian
Windows

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Linux

Data scheme

schema-free

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

yes

schema-free

Typing

predefined data types such as float or date

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

via views

SQL

Support of SQL

yes

ANSI SQL queries

yes

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

ADO.NET
JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java 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#
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

View functions in JavaScript

yes

.Net, JavaScript, C/C++

Transact SQL

View functions in JavaScript

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

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

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

yes, with always 3 replicas available

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

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

Eventual 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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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.

fine grained access rights according to SQL-standard

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