DBMS > GraphDB vs. Postgres-XL vs. RDF4J

System Properties Comparison GraphDB vs. Postgres-XL vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

Graph DBMS
RDF store

Relational DBMS

RDF store

Secondary database models

Document store
Spatial DBMS

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Trend Chart

Score	2.59
Rank	#96	Overall
	#7	Graph DBMS
	#3	RDF stores

Score	0.33
Rank	#270	Overall
	#123	Relational DBMS

Score	0.68
Rank	#223	Overall
	#9	RDF stores

Website

www.ontotext.com

www.postgres-xl.org

rdf4j.org

Technical documentation

graphdb.ontotext.com/documentation

www.postgres-xl.org/documentation

rdf4j.org/documentation

Developer

Ontotext

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

Initial release

2000

2014

since 2012, originally named StormDB

2004

Current release

10.4, October 2023

10 R1, October 2018

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

Mozilla public license

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

Java

Server operating systems

All OS with a Java VM
Linux
OS X
Windows

Linux
macOS

Linux
OS X
Unix
Windows

Data scheme

schema-free and OWL/RDFS-schema support; RDF shapes

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

SQL

Support of SQL

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

yes

distributed, parallel query execution

APIs and other access methods

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
PHP
Python

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Immediate Consistency

Foreign keys

Referential integrity

yes

Constraint checking

yes

Transaction concepts

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

ACID

MVCC

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

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Semantic Web Company and Ontotext merge to form Graphwise
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Semantic Knowledge Graphing Market to Reach USD 5.07 Billion by 2032, Driven by AI Adoption, Contextual Data Analytics, and Industry-Wide Digital Transformation | SNS Insider
17 April 2025, GlobeNewswire

Semantic Web Company and Ontotext Merge to Create Knowledge Graph and AI Powerhouse Graphwise
23 October 2024, PR Newswire

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18 December 2019, KDnuggets

A Content Management Platform and a Graph Database Come Together in the New Company: Graphwise
28 October 2024, The Recursive

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