DBMS > EventStoreDB vs. RDF4J vs. Transwarp ArgoDB

System Properties Comparison EventStoreDB vs. RDF4J vs. Transwarp ArgoDB

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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.

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

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Event Store

RDF store

Relational DBMS

Secondary database models

Search engine

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

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.07
Rank	#350	Overall
	#153	Relational DBMS

Website

www.eventstore.com

rdf4j.org

www.transwarp.cn/en/product/argodb

Technical documentation

developers.eventstore.com

rdf4j.org/documentation

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Event Store Limited

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

Transwarp

Initial release

2012

2004

Current release

21.2, February 2021

License

Commercial or Open Source

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

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

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

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

User concepts

Access control

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