DBMS > Faircom EDGE vs. mSQL vs. RavenDB vs. ToroDB

System Properties Comparison Faircom EDGE vs. mSQL vs. RavenDB vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Document store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

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

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

www.faircom.com/products/faircom-edge

hughestech.com.au/products/msql

ravendb.net

github.com/torodb/server

Technical documentation

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

ravendb.net/docs

Developer

FairCom Corporation

Hughes Technologies

Hibernating Rhinos

8Kdata

Initial release

1979

1994

2010

2016

Current release

V3, October 2020

4.4, October 2021

5.4, July 2022

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

free licenses can be provided

Open Source

AGPL version 3, commercial license available

Open Source

AGPL-V3

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

ANSI C, C++

Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

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

Linux
macOS
Raspberry Pi
Windows

All OS with a Java 7 VM

Data scheme

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

string, integer, double, boolean, date, object_id

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

A subset of ANSI SQL is implemented

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

SQL-like query language (RQL)

APIs and other access methods

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

JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

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

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

Multi-source replication

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

none

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

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

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

Authorization levels configured per client per database

Access rights for users and roles

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