DBMS > Microsoft Azure AI Search vs. RDF4J vs. Tkrzw

System Properties Comparison Microsoft Azure AI Search vs. RDF4J vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

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

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Search engine

RDF store

Key-value store

Secondary database models

Vector DBMS

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

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

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

rdf4j.org

dbmx.net/tkrzw

Technical documentation

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

rdf4j.org/documentation

Developer

Microsoft

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

Mikio Hirabayashi

Initial release

2015

2004

2020

Current release

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X
Unix
Windows

Linux
macOS

Data scheme

yes

RDF Schemas

schema-free

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

APIs and other access methods

RESTful HTTP API

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

Java
PHP
Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

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

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

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.

yes

using specific database classes

User concepts

Access control

yes

using Azure authentication

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