DBMS > AllegroGraph vs. EsgynDB vs. RDF4J vs. searchxml

System Properties Comparison AllegroGraph vs. EsgynDB vs. RDF4J vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

RDF store

Native XML DBMS
Search engine

Secondary database models

Spatial DBMS

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

Score	1.16
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

allegrograph.com

www.esgyn.cn

rdf4j.org

www.searchxml.net/category/products

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

rdf4j.org/documentation

www.searchxml.net/support/handouts

Developer

Franz Inc.

Esgyn

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

informationpartners gmbh

Initial release

2004

2015

2004

2015

Current release

8.0, December 2023

1.0

License

Commercial or Open Source

commercial

Limited community edition free

commercial

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

Java

C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Unix
Windows

Windows

Data scheme

yes

RDF schemas

yes

RDF Schemas

schema-free

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.

bulk load of XML files possible

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

APIs and other access methods

RESTful HTTP API
SPARQL

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

Java
PHP
Python

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

Java Stored Procedures

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

none

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

News

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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More resources

Recent citations in the news

Q&A: Can Neuro-Symbolic AI Solve AI’s Weaknesses?
8 April 2024, TDWI

AI predictions for 2024 unveil exciting technological horizons
21 November 2023, Wire19

Neuro-Symbolic AI: The Peak of Artificial Intelligence
16 November 2021, AiThority

Fuse Graph Neural Networks with Semantic Reasoning to Produce Complimentary Predictions
21 September 2021, Towards Data Science

Franz Releases the First Neuro-Symbolic AI Platform Merging Knowledge Graphs, Generative AI, and Vector Storage
11 December 2023, Datanami

provided by Google News

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