DBMS > Faircom EDGE vs. IBM Cloudant vs. Lovefield vs. mSQL vs. OrigoDB

System Properties Comparison Faircom EDGE vs. IBM Cloudant vs. Lovefield vs. mSQL vs. OrigoDB

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

Embeddable relational database for web apps written in pure JavaScript

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

Primary database model

Key-value store
Relational DBMS

Document store

Relational DBMS

Document store
Object oriented 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	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

www.faircom.com/products/faircom-edge

www.ibm.com/products/cloudant

google.github.io/lovefield

hughestech.com.au/products/msql

origodb.com

Technical documentation

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

cloud.ibm.com/docs/Cloudant

github.com/google/lovefield/blob/master/docs/spec_index.md

origodb.com/docs

Developer

FairCom Corporation

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Google

Hughes Technologies

Robert Friberg et al

Initial release

1979

2010

2014

1994

2009

under the name LiveDB

Current release

V3, October 2020

2.1.12, February 2017

4.4, October 2021

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache 2.0

commercial

free licenses can be provided

Open Source

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

ANSI C, C++

Erlang

JavaScript

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

hosted

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

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL queries

SQL-like query language

via JavaScript builder pattern

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

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

JDBC
ODBC

.NET Client API
HTTP API
LINQ

Supported programming languages

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

C#
Java
JavaScript
Objective-C
PHP
Ruby

JavaScript

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

View functions (Map-Reduce) in JavaScript

yes

Triggers

yes

Using read-only observers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

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

none

Source-replica replication

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

none

Foreign keys

Referential integrity

yes

when using SQL

yes

depending on model

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

Write ahead log

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

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

Role based authorization

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