DBMS > RDF4J vs. Rockset vs. Splice Machine vs. Virtuoso

System Properties Comparison RDF4J vs. Rockset vs. Splice Machine vs. Virtuoso

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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 scalable, reliable search and analytics service in the cloud, built on RocksDB

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Virtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs

Primary database model

RDF store

Document store

Relational DBMS

Document store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine

Secondary database models

Relational DBMS
Search engine

Spatial DBMS

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

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	4.26
Rank	#78	Overall
	#13	Document stores
	#4	Graph DBMS
	#2	Native XML DBMS
	#42	Relational DBMS
	#2	RDF stores
	#9	Search engines

Website

rdf4j.org

rockset.com

splicemachine.com

virtuoso.openlinksw.com

Technical documentation

rdf4j.org/documentation

docs.rockset.com

splicemachine.com/how-it-works

docs.openlinksw.com/virtuoso

Developer

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

Rockset

Splice Machine

OpenLink Software

Initial release

2004

2019

2014

1998

Current release

3.1, March 2021

7.2.11, September 2023

License

Commercial or Open Source

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

GPLv2, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Unix
Windows

hosted

Linux
OS X
Solaris
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

RDF Schemas

schema-free

yes

SQL - Standard relational schema
RDF - Quad (S, P, O, G) or Triple (S, P, O)
XML - DTD, XML Schema
DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type

Typing

predefined data types such as float or date

yes

dynamic typing

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.

ingestion from XML files supported

yes

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

Read-only SQL queries, including JOINs

yes

SQL-92, SQL-200x, SQL-3, SQLX

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP REST

JDBC
Native Spark Datasource
ODBC

ADO.NET
GeoSPARQL
HTTP API
JDBC
Jena RDF API
ODBC
OLE DB
RDF4J API
RESTful HTTP API
Sesame REST HTTP Protocol
SOAP webservices
SPARQL 1.1
WebDAV
XPath
XQuery
XSLT

Supported programming languages

Java
PHP
Python

Go
Java
JavaScript (Node.js)
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

Java

yes

Virtuoso PL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication
Source-replica replication

Chain, star, and bi-directional replication
Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

Access rights for users and organizations can be defined via Rockset console

Access rights for users, groups and roles according to SQL-standard

Fine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

More information provided by the system vendor

Specific characteristics

Virtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more

Competitive advantages

Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more

Typical application scenarios

Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more

Key customers

Broad use across enterprises and governments including — European Union (EU) US Government...
» more

Market metrics

Largest installed-base of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more

Licensing and pricing models

Available in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
» more

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

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