DBMS > Faircom EDGE vs. IBM Cloudant vs. IBM Db2 vs. Microsoft SQL Server

System Properties Comparison Faircom EDGE vs. IBM Cloudant vs. IBM Db2 vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Description

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 based on Apache CouchDB

Common in IBM host environments, 2 different versions for host and Windows/Linux

Microsofts flagship relational DBMS

Primary database model

Key-value store
Relational DBMS

Document store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Graph DBMS
Spatial DBMS

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

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

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

www.faircom.com/products/faircom-edge

www.ibm.com/products/cloudant

www.ibm.com/products/db2

www.microsoft.com/en-us/sql-server

Technical documentation

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

cloud.ibm.com/docs/Cloudant

www.ibm.com/docs/en/db2

learn.microsoft.com/en-US/sql/sql-server

Developer

FairCom Corporation

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

IBM

Microsoft

Initial release

1979

2010

1983

host version

1989

Current release

V3, October 2020

12.1, October 2016

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

free version is available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

ANSI C, C++

Erlang

C and C++

C++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
Windows

Data scheme

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

schema-free

yes

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

SQL

Support of SQL

yes

ANSI SQL queries

yes

APIs and other access methods

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

RESTful HTTP/JSON API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

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

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

View functions (Map-Reduce) in JavaScript

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

only with Windows/Unix/Linux Version

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication
Source-replica replication

yes

with separate tools (MQ, InfoSphere)

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Eventual 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

ACID

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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