DBMS > DolphinDB vs. GraphDB vs. TerminusDB

System Properties Comparison DolphinDB vs. GraphDB vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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.

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

Primary database model

Time Series DBMS

Graph DBMS
RDF store

Graph DBMS

Secondary database models

Relational DBMS

Document store
RDF store

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

Score	4.23
Rank	#82	Overall
	#6	Time Series DBMS

Score	3.10
Rank	#100	Overall
	#7	Graph DBMS
	#4	RDF stores

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Website

www.dolphindb.com

www.ontotext.com

terminusdb.com

Technical documentation

docs.dolphindb.cn/en/help200/index.html

graphdb.ontotext.com/documentation

terminusdb.github.io/terminusdb/#

Social network pages

Developer

DolphinDB, Inc

Ontotext

DataChemist Ltd.

Initial release

2018

2000

2018

Current release

v2.00.4, January 2022

10.4, October 2023

11.0.0, January 2023

License

Commercial or Open Source

commercial

free community version available

commercial

Some plugins of GraphDB Workbench are open sourced

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

C++

Java

Prolog, Rust

Server operating systems

Linux
Windows

All OS with a Java VM
Linux
OS X
Windows

Linux

Data scheme

yes

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

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.

Secondary indexes

yes

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

SQL

Support of SQL

SQL-like query language

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

SQL-like query language (WOQL)

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

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

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

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

JavaScript
Python

Server-side scripts

Stored procedures

yes

well-defined plugin interfaces; JavaScript server-side extensibility

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Foreign keys

Referential integrity

yes

Constraint checking

yes

Transaction concepts

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

yes

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

Administrators, Users, Groups

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.

Role-based access control

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

Scaling Understanding with the Help of Feedback Loops, Knowledge Graphs and NLP
19 April 2024

How Knowledge Graphs Power Data Mesh and Data Fabric
10 April 2024

Building Smarter Financial Services: The Role of Semantic Technologies, Knowledge Graphs and Generative AI
3 April 2024

Using GraphDB’s Natural Language Interface to Talk with Your Content
29 March 2024

Choosing A Graph Data Model to Best Serve Your Use Case
27 March 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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