DBMS > Microsoft Azure SQL Database vs. RDF4J vs. Stardog vs. XTDB

System Properties Comparison Microsoft Azure SQL Database vs. RDF4J vs. Stardog vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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.

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	78.40
Rank	#15	Overall
	#10	Relational DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	2.05
Rank	#129	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.09
Rank	#351	Overall
	#47	Document stores

Website

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

rdf4j.org

www.stardog.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

rdf4j.org/documentation

docs.stardog.com

www.xtdb.com/docs

Developer

Microsoft

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

Stardog-Union

Juxt Ltd.

Initial release

2010

2004

2010

2019

Current release

V12

7.3.0, May 2020

1.19, September 2021

License

Commercial or Open Source

commercial

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

Open Source

MIT License

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

Clojure

Server operating systems

hosted

Linux
OS X
Unix
Windows

Linux
macOS
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

RDF Schemas

schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

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

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

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

HTTP REST
JDBC

Supported programming languages

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

Java
PHP
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

Transact SQL

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

none

Multi-source replication in HA-Cluster

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Access rights for users and roles

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