DBMS > Microsoft Azure SQL Database vs. OpenEdge vs. RDF4J vs. Stardog vs. WakandaDB

System Properties Comparison Microsoft Azure SQL Database vs. OpenEdge vs. RDF4J vs. Stardog vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

Application development environment with integrated database management system

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

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	3.75
Rank	#88	Overall
	#47	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	#352	Overall
	#16	Object oriented DBMS

Website

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

www.progress.com/openedge

rdf4j.org

www.stardog.com

wakanda.github.io

Technical documentation

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

documentation.progress.com/output/ua/OpenEdge_latest

rdf4j.org/documentation

docs.stardog.com

wakanda.github.io/doc

Developer

Microsoft

Progress Software Corporation

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

Stardog-Union

Wakanda SAS

Initial release

2010

1984

2004

2010

2012

Current release

V12

OpenEdge 12.2, March 2020

7.3.0, May 2020

2.7.0 (April 29, 2019), April 2019

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

AGPLv3, extended commercial license available

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

C++, JavaScript

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Unix
Windows

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

RDF Schemas

schema-free and OWL/RDFS-schema support

yes

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

close to SQL 92

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

APIs and other access methods

ADO.NET
JDBC
ODBC

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

RESTful HTTP API

Supported programming languages

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

Progress proprietary ABL (Advanced Business Language)

Java
PHP
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

Transact SQL

yes

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

since Version 11.4

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

Source-replica replication

none

Multi-source replication in HA-Cluster

none

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

Immediate Consistency

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

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

Users and groups

Access rights for users and roles

yes

More information provided by the system vendor

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