DBMS > EventStoreDB vs. EXASOL vs. Faircom EDGE vs. RDF4J

System Properties Comparison EventStoreDB vs. EXASOL vs. Faircom EDGE vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

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

Primary database model

Event Store

Relational DBMS

Key-value store
Relational DBMS

RDF store

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

Score	1.14
Rank	#181	Overall
	#1	Event Stores

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	0.03
Rank	#380	Overall
	#59	Key-value stores
	#157	Relational DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

www.eventstore.com

www.exasol.com

www.faircom.com/products/faircom-edge

rdf4j.org

Technical documentation

developers.eventstore.com

www.exasol.com/resources

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

rdf4j.org/documentation

Developer

Event Store Limited

Exasol

FairCom Corporation

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

Initial release

2012

2000

1979

2004

Current release

21.2, February 2021

V3, October 2020

License

Commercial or Open Source

Open Source

commercial

Restricted, free version available

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

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Implementation language

ANSI C, C++

Java

Server operating systems

Linux
Windows

Android
Linux

ARM, x86
Raspbian
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

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

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
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

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

Foreign keys

Referential integrity

yes

when using SQL

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

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.

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