DBMS > AgensGraph vs. Kinetica vs. RDF4J vs. Valentina Server

System Properties Comparison AgensGraph vs. Kinetica vs. RDF4J vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Fully vectorized database across both GPUs and CPUs

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

Object-relational database and reports server

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

RDF store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

bitnine.net/agensgraph

www.kinetica.com

rdf4j.org

www.valentina-db.net

Technical documentation

bitnine.net/documentation

docs.kinetica.com

rdf4j.org/documentation

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Bitnine Global Inc.

Kinetica

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

Paradigma Software

Initial release

2016

2012

2004

1999

Current release

2.1, December 2018

7.1, August 2021

5.7.5

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

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, C++

Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

depending on used data model

yes

RDF Schemas

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

Cypher Query Language
JDBC

JDBC
ODBC
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ODBC

Supported programming languages

C
Java
JavaScript
Python

C++
Java
JavaScript (Node.js)
Python

Java
PHP
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

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

no, but can be realized using table inheritance

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

yes

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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