DBMS > EXASOL vs. Faircom EDGE vs. H2 vs. OpenEdge vs. RDF4J

System Properties Comparison EXASOL vs. Faircom EDGE vs. H2 vs. OpenEdge vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

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

Application development environment with integrated database management system

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

RDF store

Secondary database models

Spatial DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

www.exasol.com

www.faircom.com/products/faircom-edge

www.h2database.com

www.progress.com/openedge

rdf4j.org

Technical documentation

www.exasol.com/resources

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

www.h2database.com/html/main.html

documentation.progress.com/output/ua/OpenEdge_latest

rdf4j.org/documentation

Developer

Exasol

FairCom Corporation

Thomas Mueller

Progress Software Corporation

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2000

1979

2005

1984

2004

Current release

V3, October 2020

2.2.220, July 2023

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

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

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

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

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

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

close to SQL 92

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

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

JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java
Lua
Python
R

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

Java

Progress proprietary ABL (Advanced Business Language)

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

.Net, JavaScript, C/C++

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

none

horizontal partitioning

since Version 11.4

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

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

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

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

fine grained access rights according to SQL-standard

Users and groups

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