DBMS > DataFS vs. Faircom EDGE vs. Greenplum vs. H2 vs. STSdb

System Properties Comparison DataFS vs. Faircom EDGE vs. Greenplum vs. H2 vs. STSdb

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Object oriented DBMS

Key-value store
Relational DBMS

Relational DBMS

Key-value store

Secondary database models

Graph DBMS

Document store
Spatial DBMS

Spatial DBMS

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

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

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

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

newdatabase.com

www.faircom.com/products/faircom-edge

greenplum.org

www.h2database.com

github.com/STSSoft/STSdb4

Technical documentation

dev.mobiland.com/Overview.xsp

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

docs.greenplum.org

www.h2database.com/html/main.html

Developer

Mobiland AG

FairCom Corporation

Pivotal Software Inc.

Thomas Mueller

STS Soft SC

Initial release

2018

1979

2005

2011

Current release

1.1.263, October 2022

V3, October 2020

7.0.0, September 2023

2.2.220, July 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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.

Implementation language

ANSI C, C++

Java

Server operating systems

Windows

Android
Linux

ARM, x86
Raspbian
Windows

Linux

All OS with a Java VM

Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL queries

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

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

JDBC
ODBC

.NET Client API

Supported programming languages

.Net
C
C#
C++
VB.Net

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

C
Java
Perl
Python
R

Java

C#
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Java Stored Procedures and User-Defined Functions

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

File partitioning

Customizable business rules for partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable 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

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

yes, multi-version concurrency control (MVCC)

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

Windows-Profile

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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