DBMS > Faircom EDGE vs. Graph Engine vs. HBase vs. MySQL vs. STSdb

System Properties Comparison Faircom EDGE vs. Graph Engine vs. HBase vs. MySQL vs. STSdb

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Wide-column store based on Apache Hadoop and on concepts of BigTable

Widely used open source RDBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Key-value store
Relational DBMS

Graph DBMS
Key-value store

Wide column store

Relational DBMS

Key/Value like access via memcached API

Key-value store

Secondary database models

Document store
Spatial 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	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

www.faircom.com/products/faircom-edge

www.graphengine.io

hbase.apache.org

www.mysql.com

github.com/STSSoft/STSdb4

Technical documentation

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

www.graphengine.io/docs/manual

hbase.apache.org/book.html

dev.mysql.com/doc

Developer

FairCom Corporation

Microsoft

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Oracle

since 2010, originally MySQL AB, then Sun

STS Soft SC

Initial release

1979

2010

2008

1995

2011

Current release

V3, October 2020

2.3.4, January 2021

8.4.0, April 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

MIT License

Open Source

Apache version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPLv2, commercial license available

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.

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Implementation language

ANSI C, C++

.NET and C

Java

C and C++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

.NET

Linux
Unix
Windows

using Cygwin

FreeBSD
Linux
OS X
Solaris
Windows

Windows

Data scheme

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

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

options to bring your own types, AVRO

yes

primitive types and user defined types (classes)

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

with proprietary extensions

APIs and other access methods

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

RESTful HTTP API

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API

Supported programming languages

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

C#
C++
F#
Visual Basic

C
C#
C++
Groovy
Java
PHP
Python
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Coprocessors in Java

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

horizontal partitioning

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

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

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

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Users with fine-grained authorization concept

no user groups or roles

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