DBMS > RDF4J vs. TDSQL for MySQL vs. TerminusDB vs. TinkerGraph

System Properties Comparison RDF4J vs. TDSQL for MySQL vs. TerminusDB vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Description

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

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

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

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

RDF store

Relational DBMS

Graph DBMS

Secondary database models

Document store
Spatial DBMS

Document store
RDF store

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

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

rdf4j.org

www.tencentcloud.com/products/dcdb

terminusdb.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

rdf4j.org/documentation

www.tencentcloud.com/document/product/1042

terminusdb.github.io/terminusdb/#

Developer

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

Tencent

DataChemist Ltd.

Initial release

2004

2013

2018

2009

Current release

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

GPL V3

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Prolog, Rust

Java

Server operating systems

Linux
OS X
Unix
Windows

hosted

Linux

Data scheme

yes

RDF Schemas

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (WOQL)

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

TinkerPop 3

Supported programming languages

Java
PHP
Python

C
C#
C++
Java
PHP
Python
Ruby

JavaScript
Python

Groovy
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

Graph Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Journaling Streams

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

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 journaling

optional

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept

Role-based access control

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