DBMS > ArcadeDB vs. Microsoft SQL Server vs. OushuDB vs. RDF4J

System Properties Comparison ArcadeDB vs. Microsoft SQL Server vs. OushuDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Microsofts flagship relational DBMS

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

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

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

RDF store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.02
Rank	#374	Overall
	#52	Document stores
	#38	Graph DBMS
	#56	Key-value stores
	#38	Time Series DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

arcadedb.com

www.microsoft.com/en-us/sql-server

www.oushu.com/product/oushuDB

rdf4j.org

Technical documentation

docs.arcadedb.com

learn.microsoft.com/en-US/sql/sql-server

www.oushu.com/documentation

rdf4j.org/documentation

Developer

Arcade Data

Microsoft

Oushu

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

Initial release

2021

1989

2004

Current release

September 2021

SQL Server 2022, November 2022

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Java

Server operating systems

All OS with a Java VM

Linux
Windows

Linux

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

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

SQL

Support of SQL

SQL-like query language, no joins

yes

Full-featured ANSI SQL support

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C++

Java
PHP
Python

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

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

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Kerberos, SSL and role based access

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