DBMS > RDF4J vs. Sqrrl vs. Stardog vs. VelocityDB

System Properties Comparison RDF4J vs. Sqrrl vs. Stardog vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

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

Adaptable, secure NoSQL built on Apache Accumulo

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

RDF store

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS
RDF store

Graph DBMS
Object oriented DBMS

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

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

rdf4j.org

sqrrl.com

www.stardog.com

velocitydb.com

Technical documentation

rdf4j.org/documentation

docs.stardog.com

velocitydb.com/UserGuide

Developer

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

Amazon

originally Sqrrl Data, Inc.

Stardog-Union

VelocityDB Inc

Initial release

2004

2012

2010

2011

Current release

7.3.0, May 2020

7.x

License

Commercial or Open Source

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Java

Server operating systems

Linux
OS X
Unix
Windows

Linux

Linux
macOS
Windows

Any that supports .NET

Data scheme

yes

RDF Schemas

schema-free

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

.Net

Supported programming languages

Java
PHP
Python

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

.Net

Server-side scripts

Stored procedures

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

making use of Hadoop

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

making use of Hadoop

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Immediate Consistency in HA-Cluster

Immediate Consistency

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

Atomic updates per row, document, or graph entity

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 capabilities

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

yes

User concepts

Access control

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

Access rights for users and roles

Based on Windows Authentication

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More resources

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provided by Google News

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