DBMS > GraphDB vs. Kinetica vs. PostGIS vs. TerminusDB

System Properties Comparison GraphDB vs. Kinetica vs. PostGIS 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.

Fully vectorized database across both GPUs and CPUs

Spatial extension of PostgreSQL

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

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Relational DBMS

Document store
RDF store

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

Score	3.32
Rank	#91	Overall
	#6	Graph DBMS
	#4	RDF stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

Technical documentation

graphdb.ontotext.com/documentation

docs.kinetica.com

postgis.net/documentation

terminusdb.github.io/terminusdb/#

Social network pages

Developer

Ontotext

Kinetica

DataChemist Ltd.

Initial release

2000

2012

2005

2018

Current release

10.4, October 2023

7.1, August 2021

3.4.2, February 2024

11.0.0, January 2023

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

commercial

Open Source

GPL v2.0

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

C, C++

Prolog, Rust

Server operating systems

All OS with a Java VM
Linux
OS X
Windows

Linux

Data scheme

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.

yes

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

SQL-like DML and DDL statements

yes

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

JDBC
ODBC
RESTful HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

JavaScript
Python

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

user defined functions

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

based on PostgreSQL

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes

based on PostgreSQL

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 or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Constraint checking

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

GPU vRAM or System RAM

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 on table level

yes

based on PostgreSQL

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

Integrating GraphDB with Relational Database Systems
23 May 2024

Understanding the Graph Center of Excellence
17 May 2024

Migrating From LPG to RDF Graph Model
8 May 2024

Case study: Policy Enforcement Automation With Semantics
2 May 2024

Okay, RAG… We Have a Problem
26 April 2024

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

Related products and services

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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