DBMS > EventStoreDB vs. gStore vs. Oracle Rdb vs. RDF4J

System Properties Comparison EventStoreDB vs. gStore vs. Oracle Rdb 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.

A native Graph DBMS to store and maintain very large RDF datasets.

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

Primary database model

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

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Score	0.03
Rank	#367	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

www.eventstore.com

en.gstore.cn

www.oracle.com/database/technologies/related/rdb.html

rdf4j.org

Technical documentation

developers.eventstore.com

en.gstore.cn/#/enDocs

www.oracle.com/database/technologies/related/rdb-doc.html

rdf4j.org/documentation

Developer

Event Store Limited

Oracle, originally developed by Digital Equipment Corporation (DEC)

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

Initial release

2012

2016

1984

2004

Current release

21.2, February 2021

1.2, November 2023

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

BSD

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

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Implementation language

C++

Java

Server operating systems

Linux
Windows

Linux

HP Open VMS

Linux
OS X
Unix
Windows

Data scheme

schema-free and OWL/RDFS-schema support

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

yes

RDF Schemas

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP API
SPARQL 1.1

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C++
Java
JavaScript (Node.js)
PHP
Python

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

yes, on a single node

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

Users, roles and permissions, Role-Based Access Control (RBAC) supported

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