DBMS > GraphDB vs. Stardog vs. TerminusDB

System Properties Comparison GraphDB vs. Stardog vs. TerminusDB

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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.

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Graph DBMS
RDF store

Graph DBMS

Secondary database models

Document store
RDF store

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

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

Score	1.73
Rank	#130	Overall
	#12	Graph DBMS
	#6	RDF stores

Score	0.15
Rank	#327	Overall
	#29	Graph DBMS

Website

www.ontotext.com

www.stardog.com

terminusdb.com

Technical documentation

graphdb.ontotext.com/documentation

docs.stardog.com

terminusdb.github.io/terminusdb/#

Developer

Ontotext

Stardog-Union

DataChemist Ltd.

Initial release

2000

2010

2018

Current release

10.4, October 2023

7.3.0, May 2020

11.0.0, January 2023

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

GPL V3

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

Java

Prolog, Rust

Server operating systems

All OS with a Java VM
Linux
OS X
Windows

Linux
macOS
Windows

Linux

Data scheme

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

schema-free and OWL/RDFS-schema support

yes

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.

Import/export of XML data possible

Secondary indexes

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

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

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

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

SQL-like query language (WOQL)

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

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication in HA-Cluster

Journaling Streams

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 in HA-Cluster

Foreign keys

Referential integrity

yes

Constraint checking

yes

relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

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

yes

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.

Access rights for users and roles

Role-based access control

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More resources

Recent citations in the news

Semantic Web Company and Ontotext merge to form Graphwise
23 October 2024, Blocks and Files

Ontotext and TopQuadrant: A Powerful Partnership for Accelerated Adoption of Graph and Semantic Technologies
17 November 2023, PR Newswire

Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released
18 December 2019, KDnuggets

Ontotext's GraphDB 9.2 Supports RDF* to Match the Expressivity of Property Graphs
30 April 2020, PR Newswire UK

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

provided by Google News

How TerminusDB is commercializing its open source graph database
16 March 2021, VentureBeat

Dublin-based data collaboration tool TerminusDB raises €3.6 million in seed round
15 March 2021, Tech.eu

Bus Terminus Update – April 26th
26 April 2021, Around DB

provided by Google News

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