DBMS > DataFS vs. Microsoft Azure Synapse Analytics vs. RDF4J vs. SiteWhere

System Properties Comparison DataFS vs. Microsoft Azure Synapse Analytics vs. RDF4J vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

M2M integration platform for persisting/querying time series data

Primary database model

Secondary database models

Graph DBMS

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

newdatabase.com

azure.microsoft.com/services/synapse-analytics

rdf4j.org

github.com/sitewhere/sitewhere

Technical documentation

dev.mobiland.com/Overview.xsp

docs.microsoft.com/azure/synapse-analytics

rdf4j.org/documentation

sitewhere1.sitewhere.io/index.html

Developer

Mobiland AG

Microsoft

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

SiteWhere

Initial release

2018

2016

2004

2010

Current release

1.1.263, October 2022

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Common Public Attribution License Version 1.0

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

C++

Java

Server operating systems

Windows

hosted

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

RDF Schemas

predefined scheme

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

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP REST

Supported programming languages

.Net
C
C#
C++
VB.Net

C#
Java
PHP

Java
PHP
Python

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding, horizontal partitioning

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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.

User concepts

Access control

Windows-Profile

yes

Users with fine-grained authorization concept

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