DBMS > Microsoft Azure AI Search vs. Microsoft Azure SQL Database vs. RDF4J

System Properties Comparison Microsoft Azure AI Search vs. Microsoft Azure SQL Database vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Search-as-a-service for web and mobile app development

Database as a Service offering with high compatibility to Microsoft SQL Server

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

Primary database model

Search engine

Relational DBMS

RDF store

Secondary database models

Vector DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	5.71
Rank	#64	Overall
	#8	Search engines

Score	78.40
Rank	#15	Overall
	#10	Relational DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

azure.microsoft.com/en-us/services/search

azure.microsoft.com/en-us/products/azure-sql/database

rdf4j.org

Technical documentation

learn.microsoft.com/en-us/azure/search

docs.microsoft.com/en-us/azure/azure-sql

rdf4j.org/documentation

Developer

Microsoft

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

Initial release

2015

2010

2004

Current release

V12

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

hosted

Linux
OS X
Unix
Windows

Data scheme

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

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C#
Java
JavaScript
Python

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes, with always 3 replicas available

none

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

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.

User concepts

Access control

yes

using Azure authentication

fine grained access rights according to SQL-standard

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